Proceedings of the 8th International Conference on Movement, Health and Exercise: MoHE 2022―Refocusing on Sports and Exercise for a Post-pandemic World 9819921619, 9789819921614

Table of contents :
Preface
Contents
About the Editors
Survey on Knowledge, Attitude and Confidence (KAC) on Cardiopulmonary Resuscitation (CPR) Among Recreational Athletes in Contact Sports
1 Introduction
2 Methodology
2.1 Research Design
2.2 Participants
2.3 Ethical Consideration
2.4 Research Instrument
2.5 Data Collection and Analysis
3 Results and Discussion
3.1 Participants Demographics
3.2 Level of Knowledge, Attitude and Confidence on CPR
3.3 Comparison of Knowledge, Attitude and Confidence on CPR Between Male and Female CS Athletes
3.4 The Relationship of the CPR Knowledge Toward the Attitude and Confidence
4 Conclusion
References
Influence of Boot Studs on Rugby Players’ Sprinting Performance
1 Introduction
2 Methodology
2.1 Subject
3 Equipment
4 Procedure
5 Statistical Analysis
6 Result and Discussion
7 Conclusion
References
Influence of Receiver’s Position on Short-Serve Placement Among Double Badminton Players
1 Introduction
2 Methods
2.1 Instrument
2.2 Procedure
3 Results
3.1 Differences of Short-Serve Placement
4 Discussion
5 Conclusion
References
Effect of Kinesiology Tape Application on Shoulder Pain and Mobility Among State-Level Badminton Players
1 Introduction
2 Methods
2.1 Participants
2.2 Shoulder Pain
2.3 Shoulder Mobility
2.4 Kinesiology Tape (KT) Mapping on the Shoulder
2.5 Procedure
2.6 Statistical Analysis
3 Results
3.1 Dash
3.2 Selected Functional Movement Assessment
4 Discussion
5 Limitation
6 Conclusion
References
Effects of Wheel Depth on Individual Time Trial Performance Among Skilled Cyclists
1 Introduction
2 Material and Methods
2.1 Participants
2.2 Methodology
3 Results
4 Discussions
5 Conclusions
References
The Psychometric Properties of the Malay Version of the Depression, Anxiety and Stress Scale (DASS-21-M) Among Smokers
1 Introduction
1.1 Depression Anxiety Stress Scales (DASS-21)
1.2 Smoking and Mental Health
2 Method
2.1 Study Instruments
3 Results
4 Discussion
References
Malaysian Rugby Team Coaching Competency: A Review of Qualitative Study
1 Introduction
2 World Rugby Coaching Competence Training and Learning
3 Methods
4 Results
5 Conclusion
References
Association between Obesity Risk Knowledge and Body Mass Index among Sport Students
1 Introduction
2 Method
2.1 Study Population
2.2 Data Collection Procedure
2.3 Obesity Risk Knowledge-10 (ORK-10) Questionnaire
2.4 Statistical Analysis
3 Result
4 Discussion
References
High-Intensity Interval Training Protocols Variation Response to Immune Parameters and Cardiovascular Risk Factors: A Scoping Review
1 Introduction
2 Materials and Method
2.1 Study Design
2.2 Data Sources
2.3 Search Strategy and Data Extraction
2.4 Study Selection Criteria
3 Results
3.1 Article Retrieved
3.2 Article Characteristics
3.3 HIIT Intervention Protocols
3.4 Effect of HIIT on Immune Parameter
3.5 Effect of HIIT on Cardiovascular (CVD) Risk Factor
4 Discussion
5 Conclusion
References
Nutritional Status and Its Influence on Body Composition Among Healthy Overweight Men During COVID-19 Lockdown
1 Introduction
2 Materials and Methods
2.1 Study Design
2.2 Participants Recruitment and Data Collection Location
2.3 Diet Assessment and Questionnaire
3 Data Collection
3.1 Prediction of Energy Expenditure from Equation
3.2 Energy Balance Equation
3.3 Estimated Energy Requirement from Equation
3.4 Statistical Analyses
4 Results
4.1 Anthropometry and Body Composition of the Participants
4.2 Energy Intake, Energy Expenditure, Energy Expenditure, and Estimated Energy Requirement in Overweight Men
4.3 Association of Body Composition with Estimated Energy Requirement
4.4 Association of Body Composition with Energy Expenditure
4.5 Association of Body Composition with Energy Intake
4.6 Association of Body Composition and Energy Balance
4.7 Stepwise Linear Regression Analysis of Selected Nutritional Status with Body Composition
5 Discussion
6 Conclusion
References
Development of an Instrument for Assessing Knowledge, Attitude, and Practices of PE Teachers Towards COVID-19 Pandemic: A Rasch Measurement Approach
1 Introduction
2 Methods
2.1 Instrument Development and Validation Processes
2.2 The Rasch Measurement Model
2.3 Expert Judgement (Face and Content Validity)
2.4 Validity of the CVIS Instrument
2.5 Reliability of the CVIS Instrument
2.6 Item Difficulty Levels
2.7 Item Fit
2.8 Rating Scales Analysis
3 Conclusion
References
Enhancing Sustainable Tourism in Kundasang Through Hiking
1 Introduction
2 Method
2.1 Survey Instrument
2.2 Research Design and Sample
3 Data Analysis
3.1 Anova Analysis
3.2 Regression Analysis
4 Discussion and Conclusion
References
Effect of the HoPA Program on Body Mass Index and Physical Activity Level Among Children
1 Introduction
2 Methodology
3 Result
4 Discussion
5 Conclusion
References
Relationship of Personality Traits and Competitive Trait Anxiety in Recreational Individual Event Sports
1 Introduction
2 Methodology
2.1 Participants
2.2 Instrumentation
2.3 Statistical Methods
3 Results
3.1 Correlations Between Personality Traits and Competitive Trait Anxiety
3.2 Predicting Competitive Trait Anxiety from Personality Traits
4 Discussion
4.1 Correlation Between Personality Trait and Competitive Trait Anxiety
4.2 Predicting Competitive Trait Anxiety from Personality Traits
4.3 Moderation Effect of Gender
5 Conclusion
References
Determination of Essential Performance Indicator for Football for Discriminating Between Winner, Draw, and Loser Matches in Malaysia Super League 2021
1 Introduction
2 Methodology
2.1 Participants and Study Design
2.2 Principal Component Analysis
2.3 The Application of Discriminant Analysis
3 Result and Discussion
4 Conclusion
References
Secondary School Students’ Perceptions of Motivational Climate, Enjoyment Processes, and Mental Well-being in Physical Education
1 Introduction
2 Methods
2.1 Participants
2.2 Measures
2.3 Procedures
2.4 Statistical Analysis
3 Results
4 Discussion
5 Conclusion
References
Relationship Between Digit Ratio (2D:4D) and Anaerobic-based Physical Fitness Tests in Children
1 Introduction
2 Methodology
2.1 Subject Selection
2.2 Assessment of 2D:4D
2.3 Assessment of Physical Fitness
2.4 Statistical Analysis
3 Results
3.1 Comparison of 2D:4D Between Male and Female
3.2 Relationship of Age and BMI Towards to Digit Ratio
3.3 Comparison Between Low and High Digit Ratio on Anaerobic Physical Fitness
4 Discussion
4.1 Comparison the Status of 2D:4D on Male and Female
4.2 Effect of Age and BMI on 2D:4D
4.3 Comparison Between Low and High 2D:4D on Anaerobic Physical Fitness
5 Conclusion
References
Sports Fan’s Motivation among Tunku Abdul Rahman University College (TARUC) Students—An Overview
1 Introduction
2 Purpose of Study
3 Significance of Study
4 Methods
5 Findings
6 Summary
7 Recommendation
8 Contribution of Authors
References
Differences of Knee Flexion Angle at Landing Between Dynamic Tasks: Implication Towards ACL Injury Screening in Females
1 Introduction
2 Methods
2.1 Instrumentation
2.2 Procedures
2.3 Kinematic Assessment of the Dynamic Tasks
2.4 Data Analysis
3 Results
4 Discussion
References
Changes on EEG Power Spectrum with Carbohydrate Mouth Rinsing
1 Introduction
2 Methods
2.1 Participants
2.2 Experimental Protocol
2.3 EEG Data Acquisition, Processing, and Future Extraction
2.4 Mouth Rinsing Solution and Procedures
2.5 Statistical Analysis
3 Results
4 Discussion
5 Conclusion
References
Comparisons of Physical Activity Patterns in Children with Autism Spectrum Disorder and Typically Developing Children
1 Introduction
2 Methods
2.1 Participants
2.2 Measurements
2.3 Data Analysis
3 Result
4 Discussion
5 Limitation
6 Recommendation
7 Conclusion
References
Effects of Core Stability Training Among Low Back Pain Malaysian Elite Sailor Athletes
1 Introduction
1.1 Problem Statement
2 Methodology
2.1 Research Design
2.2 Participants
2.3 Sample Size
2.4 Research Procedure
2.5 Statistical Analysis
3 Results
3.1 Physical Characteristics of Participants
3.2 Pain Threshold
3.3 2000-m Rowing Performance
3.4 Isometric Back-Leg Strength
3.5 Flexor Endurance
4 Discussion
4.1 Pain Threshold
4.2 Rowing Performance
4.3 Isometric Back Strength
4.4 Flexor Endurance
5 Conclusion
References
Comparison of Ballet Barre and Center Training on Lower-Limb Active Flexibility and Dynamic Balance in Young Recreational Rhythmic Gymnasts
1 Introduction
2 Methods
2.1 Participants
2.2 Procedure
2.3 Statistical Analysis
3 Results
4 Discussion
5 Conclusion
References
The Effect of Short-Duration Resistance Training Voluntary to Failure on Muscle Adaptation of Men in Overweight
1 Introduction
2 Methods
2.1 Ethical Approval
2.2 Participants
2.3 Study Protocol
2.4 Resistance Training Intervention
2.5 Data Analysis
3 Results
4 Discussion
5 Conclusion
References
Understanding Emotional Intelligence and Personality to Athletes’ Performances: a Systematic Literature
1 Introduction
2 Method
3 Result
4 Discussion
5 Conclusion
References
Association of Arch Height of the Foot and Jump Capacity in Youth Soccer Athletes
1 Introduction
2 Methodology
2.1 Participants
2.2 Arch Height Index (AHI)
2.3 Jump Capacity
2.4 Statistical Analysis
3 Results
3.1 BMI, Foot Instep Height, and Total Foot Length
3.2 Jump Capacity
3.3 Association Between AHI and Jump Capacity
4 Discussion
5 Conclusion
References
The Relationship Between Leg Preference and Bilateral Asymmetry in Muscular Strength Among Taekwondo Athletes
1 Introduction
1.1 Background of Study
1.2 Research Problem
2 Participants
3 Methodology
3.1 Introduction
3.2 Research Design
3.3 Population/Sample/Subjects/Sampling Techniques
3.4 Instrumentation
3.5 FIFA Standard Soccer Ball
3.6 Data Collection (Procedures)
3.7 Data Analysis
3.8 Sample Size
4 Results
5 Discussion
References
Coaches’ Needs Satisfaction, Psychological Needs Thwarting and Motivation in Coaching
1 Introduction
2 Methods
2.1 Participants and Procedure
2.2 Measure
2.3 Data Analysis
3 Results
4 Discussion
5 Conclusion
References
Investigation of Coaching Effectiveness and Perfectionist in Sports: A Systematic Review
1 Introduction
2 Methodology
3 Results
4 Discussion
5 Conclusion
References
Effect of Both Side up Ball and the Biodex Balance System Training on Static and Dynamic Balance Among Overweight Sedentary Collegiate Males
1 Introduction
2 Materials and Methods
2.1 Study Design
2.2 Participants
2.3 Design and Procedures
2.4 Training Procedures
2.5 Statistical Analyzes
3 Results
4 Discussion
References
The Effects of Foam Rolling on Flexibility and Hip Range of Motion Among Individuals with Different Body Mass Index (BMI)
1 Introduction
2 Methodology
3 Results
4 Discussion
References
Effect of Cordyceps Militaris, Arginine and Citrulline Supplementation on Long Distance Runners in Hot Conditions
1 Introduction
2 Methods
2.1 Subject
2.2 Experimental Design
2.3 Preliminary Testing
2.4 Experimental Trials
2.5 Statistical Analysis
3 Results
3.1 Time to Exhaustion
3.2 Heart Rate Responses
3.3 Oxygen Uptake (VO2) Responses
3.4 Thermoregulatory Response (Core Temperature and Skin Temperature)
3.5 Perceptual Responses (RPE and Thermal Sensation)
4 Discussion
5 Conclusion
References

Citation preview

Lecture Notes in Bioengineering

Mohd Hasnun Arif Hassan · Ahmad Munir Che Muhamed · Nik Shanita Safii · Lian Yee Kok · Raja Mohammed Firhad Raja Azidin · Noor Azuan Abu Osman · Roosfa Hashim   Editors

Proceedings of the 8th International Conference on Movement, Health and Exercise MoHE 2022—Refocusing on Sports and Exercise for a Post-pandemic World

Lecture Notes in Bioengineering Advisory Editors Nigel H. Lovell, Graduate School of Biomedical Engineering, University of New South Wales, Kensington, NSW, Australia Luca Oneto, DIBRIS, Università di Genova, Genova, Italy Stefano Piotto, Department of Pharmacy, University of Salerno, Fisciano, Italy Federico Rossi, Department of Earth, University of Salerno, Fisciano, Siena, Italy Alexei V. Samsonovich, Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA Fabio Babiloni, Department of Molecular Medicine, University of Rome Sapienza, Rome, Italy Adam Liwo, Faculty of Chemistry, University of Gdansk, Gdansk, Poland Ratko Magjarevic, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

Lecture Notes in Bioengineering (LNBE) publishes the latest developments in bioengineering. It covers a wide range of topics, including (but not limited to): • • • • • • • • • • •

Bio-inspired Technology & Biomimetics Biosensors Bionanomaterials Biomedical Instrumentation Biological Signal Processing Medical Robotics and Assistive Technology Computational Medicine, Computational Pharmacology and Computational Biology Personalized Medicine Data Analysis in Bioengineering Neuroengineering Bioengineering Ethics

Original research reported in proceedings and edited books are at the core of LNBE. Monographs presenting cutting-edge findings, new perspectives on classical fields or reviewing the state-of-the art in a certain subfield of bioengineering may exceptionally be considered for publication. Alternatively, they may be redirected to more specific book series. The series’ target audience includes advanced level students, researchers, and industry professionals working at the forefront of their fields. Indexed by SCOPUS, INSPEC, zbMATH, SCImago.

Mohd Hasnun Arif Hassan · Ahmad Munir Che Muhamed · Nik Shanita Safii · Lian Yee Kok · Raja Mohammed Firhad Raja Azidin · Noor Azuan Abu Osman · Roosfa Hashim Editors

Proceedings of the 8th International Conference on Movement, Health and Exercise MoHE 2022—Refocusing on Sports and Exercise for a Post-pandemic World

Editors Mohd Hasnun Arif Hassan Faculty of Mechanical and Automotive Engineering Technology Universiti Malaysia Pahang Pekan, Pahang, Malaysia Nik Shanita Safii Faculty of Health Sciences Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia Raja Mohammed Firhad Raja Azidin Faculty of Sports Science and Recreation Universiti Teknologi MARA Shah Alam, Selangor, Malaysia

Ahmad Munir Che Muhamed Advanced Medical and Dental Institute Universiti Sains Malaysia Kepala Batas, Pulau Pinang, Malaysia Lian Yee Kok Department of Sport Science Tunku Abdul Rahman University of Management and Technology Kuala Lumpur, Malaysia Noor Azuan Abu Osman Department of Biomedical Engineering, Faculty of Engineering University of Malaya Kuala Lumpur, Malaysia

Roosfa Hashim Kulliyyah of Information and Communication Technology International Islamic University Malaysia Kuala Lumpur, Malaysia

ISSN 2195-271X ISSN 2195-2728 (electronic) Lecture Notes in Bioengineering ISBN 978-981-99-2161-4 ISBN 978-981-99-2162-1 (eBook) https://doi.org/10.1007/978-981-99-2162-1 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

The 8th International Conference on Movement, Health and Exercise (MoHE) was held on 27–29 September 2022 in Melaka, Malaysia. MoHE Conference is organised by the Malaysian Movement, Health and Exercise (MoHE Journal—published by Wolters Kluwer—mohejournal.org) and supported by the Sports Section, Policy Planning and Research Division, Ministry of Higher Education Malaysia. The theme of the 2022 MoHE Conference is “Refocusing on Sports and Exercise for a Post-pandemic World” and featured keynote addressors from internationally renowned speakers in various sports and exercise sub-disciplines. This conference serves to bring together sports scientists, researchers, and practitioners from various backgrounds to share and disseminate current research updates and evidence-based findings. Conference participants presented their research according to sub-themes such as Physical Activity and Health, Exercise Science, Human Performance, Sports Nutrition, Sports Medicine, Sports Technology, and Management and Sports Studies. Pekan, Malaysia Kepala Batas, Malaysia Kuala Lumpur, Malaysia Kuala Lumpur, Malaysia Shah Alam, Malaysia Kuala Lumpur, Malaysia Kuala Lumpur, Malaysia

Mohd Hasnun Arif Hassan Ahmad Munir Che Muhamed Nik Shanita Safii Lian Yee Kok Raja Mohammed Firhad Raja Azidin Noor Azuan Abu Osman Roosfa Hashim

v

Contents

Survey on Knowledge, Attitude and Confidence (KAC) on Cardiopulmonary Resuscitation (CPR) Among Recreational Athletes in Contact Sports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fairus Fariza Zainudin, Nur Syahirah Faizul Azman, Fariba Hossein Abadi, Mohansundar Sankaravel, Nor Fadila Kasim, and Nurul Uyun Abdul Aziz Influence of Boot Studs on Rugby Players’ Sprinting Performance . . . . . Sharul Nizam Turiman and Nasrul Hadi Johari Influence of Receiver’s Position on Short-Serve Placement Among Double Badminton Players . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Allan Ivan Mauming and Raihana Sharir Effect of Kinesiology Tape Application on Shoulder Pain and Mobility Among State-Level Badminton Players . . . . . . . . . . . . . . . . . . Radin Rafeeuddin Radin Dzulfakar, Fariha Sofiya Mohd Shufaian, and Raihana Sharir Effects of Wheel Depth on Individual Time Trial Performance Among Skilled Cyclists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohd Azka Nabil, Hosni Hasan, Mohd Shariman Ismadi Ismail, and Mohd Azim Nural Azhan The Psychometric Properties of the Malay Version of the Depression, Anxiety and Stress Scale (DASS-21-M) Among Smokers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nur-Hasanah Ruslan, Nur Amirah Fikriyah Muhd Suhaidi, and Siti Munira Yasin Malaysian Rugby Team Coaching Competency: A Review of Qualitative Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ahmad Fadzlee Ahmad Idriss, Mohar Kassim, and Ahmad Effendy Abdul Razak

1

11

21

31

41

49

59

vii

viii

Contents

Association between Obesity Risk Knowledge and Body Mass Index among Sport Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alya Natasha Rozzaini, Farhanah Abdul Rahman, Nur Asmidar A. Halim, and Noor Fatihah Ilias High-Intensity Interval Training Protocols Variation Response to Immune Parameters and Cardiovascular Risk Factors: A Scoping Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nik Siti Nik Zaid, Ayu S. Muhamad, Mohd Nidzam Jawis, Foong Kiew Ooi, Mahaneem Mohamed, Rohimah Mohamud, and Normah Jusoh

77

87

Nutritional Status and Its Influence on Body Composition Among Healthy Overweight Men During COVID-19 Lockdown . . . . . . . . . . . . . . . 119 Nursharlina Sharan, Nur Syamsina Ahmad, Nur Dalila Adilah Abdul Raof, and Nurulezah Hasbullah Development of an Instrument for Assessing Knowledge, Attitude, and Practices of PE Teachers Towards COVID-19 Pandemic: A Rasch Measurement Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Voon Mui Yee and Chin Ngien Siong Enhancing Sustainable Tourism in Kundasang Through Hiking . . . . . . . 147 Mohamad Nizam Bin Nazarudin, Muhammad Azim Bin Abdul Rahim, and Norlaila Azura Binti Kosni Effect of the HoPA Program on Body Mass Index and Physical Activity Level Among Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Wan Mohd Norsyam, Nurul Diyana Sanuddin, Norlaila Azura Kosni, Mohd Zulkhairi Mohd Azam, and Maisarah Mohd Saleh Relationship of Personality Traits and Competitive Trait Anxiety in Recreational Individual Event Sports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 Kleven Jin Yew Lim and Kang Mea Kee Determination of Essential Performance Indicator for Football for Discriminating Between Winner, Draw, and Loser Matches in Malaysia Super League 2021 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Muhammad Azim Abdul Rahim, Norlaila Azura Kosni, and Mohamad Nizam Nazarudin Secondary School Students’ Perceptions of Motivational Climate, Enjoyment Processes, and Mental Well-being in Physical Education . . . . 191 Teo Boon Sian, Chin Ngien Siong, and Matheus Chin Yan Yu

Contents

ix

Relationship Between Digit Ratio (2D:4D) and Anaerobic-based Physical Fitness Tests in Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Zulkhairi Azam, Zainal Abidin Zainuddin, Fatin Nadhirah Binti Zulkiflee, Nurul Diyana Binti Sanuddin, Norlaila Azura Binti Kosni, and Fatin Aqilah Binti Razak Sports Fan’s Motivation among Tunku Abdul Rahman University College (TARUC) Students—An Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Tracy Tan Li Jing and Tan Chee Hian Differences of Knee Flexion Angle at Landing Between Dynamic Tasks: Implication Towards ACL Injury Screening in Females . . . . . . . . . 237 Raihana Sharir, Muhammad Adam Mohd Nor Abadi, Mark A. Robinson, Jos Vanrenterghem, and Radin Rafeeuddin Radin Dzulfakar Changes on EEG Power Spectrum with Carbohydrate Mouth Rinsing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Harris Kamal Kamaruddin, Al-Hafiz Abu Bakar, Nurul Farha Zainuddin, Mohammad Shahril Salim, and Saidatul Ardeenawatie Awang Comparisons of Physical Activity Patterns in Children with Autism Spectrum Disorder and Typically Developing Children . . . . . . . . . . . . . . . . 257 Wei Joo Chen, Ahmad Nabilatulhuda, and Nor M. F. Farah Effects of Core Stability Training Among Low Back Pain Malaysian Elite Sailor Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 Nurul Afiqah Bakar, Wan Amirul Hafiy Wan Rosli, Nur Firzanah Azrul Hisham, and Nurul Hidayah Amir Comparison of Ballet Barre and Center Training on Lower-Limb Active Flexibility and Dynamic Balance in Young Recreational Rhythmic Gymnasts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279 See Beatrice Qin Thon and Kok Lian-Yee The Effect of Short-Duration Resistance Training Voluntary to Failure on Muscle Adaptation of Men in Overweight . . . . . . . . . . . . . . . 293 Nur Dania Rosaini, Siti Syahirah Aqilah Shafee, Al-Hafiz Abu Bakar, Norazwan Mokhtar, Harris Kamal Kamaruddin, and Ahmad Dzulkarnain Ismail Understanding Emotional Intelligence and Personality to Athletes’ Performances: a Systematic Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 Nur Afifah Saufi, Ahmad Fikri Mohd Kassim, and Siti Hannariah Mansor

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Contents

Association of Arch Height of the Foot and Jump Capacity in Youth Soccer Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325 Shariman Ismadi Ismail, Fatin Sabrina Nor Azian, Rahmat Adnan, Siti Zulaikha Kamil, Amir Adri Nun Arimanshah, Norasrudin Sulaiman, Motohide Arayama, Raja Mohammed Firhad Raja Azidin, Johan Kamal Hamidon, Mohamad Mohd Sadek Mustafa, and Mohad Anizu Mohd Nor The Relationship Between Leg Preference and Bilateral Asymmetry in Muscular Strength Among Taekwondo Athletes . . . . . . . . 335 Sarina Md Yusof and Muhd Ithar Haziq Coaches’ Needs Satisfaction, Psychological Needs Thwarting and Motivation in Coaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 Chin Ngien Siong, Teo Boon Sian, and Voon Mui Yee Investigation of Coaching Effectiveness and Perfectionist in Sports: A Systematic Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361 Nurfatehah Ahmad Nasir, Ahmad Fikri Mohd Kassim, and Nurul Farha Zainuddin Effect of Both Side up Ball and the Biodex Balance System Training on Static and Dynamic Balance Among Overweight Sedentary Collegiate Males . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387 Tan S. Han, Y. Ashril, and Khong T. Keen The Effects of Foam Rolling on Flexibility and Hip Range of Motion Among Individuals with Different Body Mass Index (BMI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 397 J. M. Wong, P. Y. Lian, K. Q. Chan, T. K. Khong, and A. Yusof Effect of Cordyceps Militaris, Arginine and Citrulline Supplementation on Long Distance Runners in Hot Conditions . . . . . . . . 407 Hui Yin Ler, Jian Yun Tan, and Kai Quin Chan

About the Editors

Dr. Mohd Hasnun Arif Hassan earned his first degree in Mechanical Engineering from the University of Applied Sciences Bingen, Germany, in 2010. During the final year of his undergraduate study, he was offered a scholarship by Universiti Malaysia Pahang (UMP) to pursue a Master’s degree in Mechanical Engineering at the University of Malaya in Kuala Lumpur, which he graduated with distinction in 2012. After that, he embarked on his Ph.D. journey at UMP where he studied about the head injury sustained by soccer players due to heading manoeuvre. He completed his Ph.D. study in 2016, then continue to serve UMP as a senior lecturer. His research interests include finite element modelling of the interaction between human and sports equipment, instrumentation of sports equipment and injury prevention particularly with regard to sports and traffic accidents. His work aims to apply engineering principles in sports not only to enhance the performance of an athlete but also to prevent injuries. Besides research work, Hasnun also involves in managing journals, namely the Movement, Health and Exercise (MoHE Journal) under the Ministry of Education of Malaysia, where he now serves as a section editor. He is also the founding editorin-chief of Mekatronika, a UMP mechatronics journal, and also currently serves as one of the coordinators of Open Journal System (OJS) in UMP. He considers himself a computer geek who enjoys graphic design and website development. Hasnun also loves music and plays guitar, bass and/or drum occasionally. Assoc. Prof. Dr. Ahmad Munir Che Muhamed is an associate professor in Sport and Exercise Science at the Lifestyle Science Research Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang. His academic endeavour started in 1990 when he was awarded the Federal Sports Scholarship by the Ministry of Youth and Sport Malaysia. He received his Bachelor and Master of Science Degree from Indiana State University in Exercise Science in 1994 and 1996, respectively. He then completed his doctoral studies in Exercise and Sports Science at the University of Sydney in 2005. His primary research interest includes environmental exercise

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About the Editors

physiology where he had examined the influence of relative humidity in the development of heat stress and its effect on sports performance. In addition, Dr. Munir had also examined circulatory and muscular physiological responses to exercise. He has presented his research findings in several national and international scientific conferences. A former national and intercollegiate athlete at Indiana State University, Dr. Munir competed in Division I NCAA Men’s Tennis competition for four years. Dr. Munir remains active in consultancy work relating to Sport Science within several government agencies. He was previously the chairman of National Coaching Board, Malaysia, from 2009–2011. Assoc. Prof. Dr. Nik Shanita Safii joined the Department of Nutrition and Dietetics, Faculty of Allied Health Sciences, UKM, as a tutor till 1996 and currently is a dietetic lecturer in the Dietetics program and a chair of the Centre for the Community Health Studies, Faculty of Health Sciences, UKM, since January 2022. Her past and current experiences are giving lectures on sports nutrition, medical nutrition therapy, healthy lifestyles, conducting weight management camps and counselling out-patients at the UKM Medical Centre. Her specialisation is web- and mobile app development on dietary assessment, training and energy requirement among athletes and active individuals (NutriSportExTM, DietScoreTM and iDietScoreTM) and determining glycemic index value of carbohydrate-containing foods and the nutritional status of specific groups. Nik Shanita is a consultant and panel to review sports science level 1–3 curriculum for coaches and teachers under the National Sports Council of Malaysia (NSC). She also delivers sports nutrition lectures in the Continuous Coach Education (CCE) NSC program. She has just been awarded as an honorary fellow of the Malaysian Dietitians Association and a life member, past honorary treasurer and honorary auditor of the Malaysian Association for the Study of Obesity. Assoc. Prof. Dr. Lian Yee Kok has a Bachelor of Education (Physical Education) and a Masters in Science (Sports Science) from Universiti Putra Malaysia (UPM) and a doctoral degree specialising in Exercise Physiology (Physical Conditioning) from the University of Western Australia. Dr. Kok was a PE teacher for five years before working as a faculty member at UPM beginning 1997 until she moved to her current employment at Tunku Abdul Rahman University of Management and Technology (TAR UMT) in 2020 as an associate professor at the Department of Sport Science, Faculty of Applied Sciences. Dr. Kok has taught courses related to exercise physiology, physical conditioning and coaching methodology in PE and sports and has been involved in research concerning optimization of performance for elite athletes, strength and conditioning methods for different sports, testing and evaluation for sports and exercise, and more recently, research related to training practices during the COVID-19 pandemic with a world-wide group of researchers. Her research has been published in journals such as Medicine and Science in Sports and Exercise, Sports Medicine, Journal of Strength and Conditioning Research, Journal of Exercise Rehabilitation and the Journal of Human Kinetics. Dr. Kok has also been an advisor to the National Sports Council Malaysia, National Institute of Sport Malaysia and the Johor State Sports Council, in addition to being a past president

About the Editors

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of the Society of Health and Physical Educators, Malaysia. At the ASEAN level, Dr. Kok is one of the founders of the ASEAN Council for PE and Sports (ACPES) and was a secretary-general for many years before becoming an advisor recently. These positions have allowed her to speak on numerous occasions on topics related to training and coaching. Dr. Kok is currently the vice president of the Malaysian Netball Association and, as an athlete, represented Malaysia in the first Asian netball championships where Malaysia finished as champions. Dr. Kok also coached the Malaysian netball team from 1999 until 2002, when she helped the national team obtain the best ranking in the 1999 world netball championships, and Malaysia’s first gold medal in netball during the 2001 Kuala Lumpur SEA Games. For this, she was named “Coach of the Year (Female, High Performance Athletes) by the National Sports Council in 2002. In addition to that, she has helped the National Coaching Academy, and sports associations develop their coaching manuals and coach development programs. Currently, Dr. Kok is actively involved in improving coach education in Malaysia. Assoc. Prof. Dr. Raja Mohammed Firhad Raja Azidin is an associate professor at the Faculty of Sport Science and Recreation, Universiti Teknologi MARA (UiTM). He completed his Ph.D. at Liverpool John Moores University (LJMU), UK, focusing on developing biomechanical and neuromuscular injury risk assessment. He is also interested in strength and conditioning for high-performance athletic success. He currently serves as the head of Strength and Conditioning for Selangor Football Club, competing in Malaysia Professional Super League. He oversees the physical conditioning department of the club with a particular focus on players’ footballspecific physical development and monitoring training load, together with initiating applied research in football-related areas. He has published several peer-reviewed journal articles on the influence of fatigue on biomechanical and neuromuscular markers of injury risk during dynamic tasks and developing injury risk assessment for injury prevention, screening, rehabilitation and return to play. His current research interest is developing high-performance physical conditioning interventions for elite athletes. Prof. Ir. Dr. Noor Azuan Abu Osman graduated from University of Bradford, UK, with a B.Eng. Hons. in Mechanical Engineering, followed by M.Sc. and Ph.D. in Bioengineering from University of Strathclyde, UK. Azuan’s research interests are quite wide ranging under the general umbrella of biomechanics. However, his main interests are the measurements of human movement, prosthetics design, the development of instrumentation for forces and joint motion, and the design of prosthetics, orthotics and orthopaedic implants. In 2004, he received BLESMA award from ISPO UK NMS in recognition of his significant contribution to the development of the prosthetic socket. He is currently the deputy president of Society of Medical and Biological Engineering (MSMBE), affiliated organisations of International Federation for Medical and Biological Engineering (IFMBE). He is currently the dean of Engineering and also the deputy director of Centre for Applied Biomechanics and the Coordinator of Motion Analysis Laboratory, Faculty of Engineering, University

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About the Editors

of Malaya. He has publications in books, conference proceedings and journals. He is also a chartered engineer (C.Eng.) and fellow (FIMechE) with the Institute of Mechanical Engineers, UK, chartered professional engineer (C.Peng.) and fellow (FIEAust) with Engineers Australia. Assoc. Prof. Dr. Roosfa Hashim is a lecturer, writer, editor, publisher and publishing trainer with more than thirty-year experiences in publishing. He is the author of four writing and publishing manuals, four biographies and five research based books. Roosfa has also collaborated with several authors on three co-edited works. After a successful career in publishing, Roosfa now coaches other people to achieve the same success. He offers a wide range of publishing programs and services—from writing and editing to proofreading and indexing. Currently, Roosfa is the director of International Islamic University Malaysia Press. Prior to this, Roosfa spent more than twenty years as an editor and lecturer at National University of Malaysia (Universiti Kebangsaan Malaysia—UKM). Roosfa is also teaching at the Department of Library and Information Sciences, Kulliyyah of Information Communication and Technology, International Islamic University Malaysia. At the international publishing arena, Roosfa Hashim is a board member of the International Union of Islamic Book Publishers (IUIBP) based in Istanbul, Turkey.

Survey on Knowledge, Attitude and Confidence (KAC) on Cardiopulmonary Resuscitation (CPR) Among Recreational Athletes in Contact Sports Fairus Fariza Zainudin, Nur Syahirah Faizul Azman, Fariba Hossein Abadi, Mohansundar Sankaravel, Nor Fadila Kasim, and Nurul Uyun Abdul Aziz Abstract The incidence of Sudden Cardiac Arrest (SCA) in sports is about 0.76 cases per 100,000 athletes-year with 43% chances of surviving. The chance of survival following SCA depends hugely on CPR awareness. However, the level of knowledge, attitude and confidence (KAC) in CPR is not well known among Malaysian recreational contact sports (CS) athletes. Then, this study aims to determine the level of KAC in CPR among CS athletes. A cross-sectional survey using a snowball sampling method was used to recruit a total of 90 (46 females, 44 males) CS athletes. A self-administered questionnaire consisting of knowledge, attitude and confidence on CPR with using a Likert scale was conducted among participants. Descriptive statistics and Independent t tests were used to identify the different levels of KAC between males and females. In addition, Pearson correlation was used to analyze the relationship between knowledge toward attitude and confidence. The study results showed that 48% of respondents have attended the CPR Course. The total score of the knowledge was 57.64 (±27.46), attitude 76.36 (±11.43) and confidence 64.18 (±20.07). There was no significant difference between the gender for level of knowledge (p = 0.434). However, a significant difference was found between males and females for the level of attitude (p = 0.031) and confidence (p = 0.018). Electronic supplementary material The online version of this chapter (https://doi.org/10.1007/978-981-99-2162-1_1) contains supplementary material, which is available to authorized users. F. F. Zainudin (B) · N. S. Faizul Azman · F. H. Abadi · M. Sankaravel Department of Health Science, Faculty of Sports Science and Coaching, Universiti Pendidikan Sultan Idris, 35900 Tanjong Malim Perak, Malaysia e-mail: [email protected] N. F. Kasim Department of Coaching Science, Faculty of Sports Science and Coaching, Universiti Pendidikan Sultan Idris, 35900 Tanjong Malim Perak, Malaysia N. U. Abdul Aziz Anatomy Working Group, Faculty of Medical Sciences, Newcastle University Medicine Malaysia (NUMed), Iskandar Puteri, Johor, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_1

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F. F. Zainudin et al.

A significant correlation was found for knowledge toward attitude (r = 0.474) and confidence (r = 0.406). In conclusion, there is an inadequacy of knowledge, attitude and confidence in CPR among CS athletes. It seems that more studies on KAC and practice of CPR among CS athletes with larger sample size are required to warrant this study finding. Keywords Sudden cardiac arrest · CPR · Knowledge · Attitude · Confidence · Contact sports

1 Introduction It is well known that one of the major causes of death in industrialized nations is cardiac arrest, which is a major health problem. The survival of the victim in out-ofhospital cardiac arrest (OHCA) depends on the overall support and rapid response of a person called a bystander. It cannot be overstated how critical rapid resuscitation is to saving the lives of these individuals. The percentage of cardiac arrest patients who receive CPR ranges from 5 to 80% worldwide. If resuscitation is started immediately afterward, the likelihood of survival can increase by a factor of two to four times (Nord 2017). On the other hand, athletes who participate in sporting competitions, as well as recreational athletes in general, are usually in good health and are considered the healthiest people (Narayanan et al. 2017). Moreover, the benefits of regular exercise for the primary and secondary prevention of cardiovascular disease are well documented (Chandra et al. 2013). Contrary to popular belief, athletes with latent cardiovascular problems are more prone to exercise-induced sudden cardiac death (SCD). The study by Ozbilgin et al. (2016) found that competitive athletes have a 2.8fold higher risk of sudden cardiac death compared to non-athletes. They reported that football, due to its dynamic nature, is generally comparable to swimming, tennis, basketball and other sports where participants are at risk of sudden cardiac death (Ozbilgin et al. 2016). A similar study also showed that basketball (405 deaths) and volleyball (10 deaths) together with football (565) had the highest percentage of cardiovascular-related deaths (Akinremi 2014). However, a recent study found that 64% of high school athletes with SCA survived to hospital discharge. This is due to the fact that rapid cardiopulmonary resuscitation (CPR) was performed, which probably plays an important role. In this context, the early use of automated external defibrillators (AEDs) may be a major reason for the higher survival rate. It should be mentioned that in this study 94% of patients received CPR before an AED was used. This trend could be positively influenced by the high school team athletes’ and officials’ knowledge of cardiopulmonary resuscitation, which has been shown to reduce the number of deaths associated with cardiac arrest. Thus, knowing the necessary steps to resuscitate and recognizing cardiac arrest can be useful (Akinremi 2014). Halabchi et al. (2011) also found that more than 90% of cardiac arrests occur during or after training or competition (Halabchi et al. 2011).

Survey on Knowledge, Attitude and Confidence (KAC) …

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However, there is little published data on CPR knowledge in athletes (Akinremi 2014). Therefore, it is critical for contact athletes, who are at higher risk of myocardial infarction during training, to know, recognize and perform effective CPR on the field. We hypothesize that early CPR training will influence attitudes to improve confidence in performing CPR when SCA is imminent (Pivaˇc et al. 2020). This study focuses on understanding the current level of KAP of CPR in contact athletes. Although the likelihood of getting SCA is very low in contact sports, an individual’s ability to manage a life-threatening emergency is very important. Therefore, this study aimed to determine the level of knowledge, attitude and confidence in cardiopulmonary resuscitation (CPR) in CS athletes. The specific objectives were to determine the level of knowledge, attitude and confidence regarding CPR and to compare the difference in the level of knowledge, attitude and confidence among the different genders and finally to assess the relationship between knowledge, attitude and confidence among the CS athletes.

2 Methodology 2.1 Research Design The current study was a cross-sectional survey to assess respondents’ knowledge, attitudes and confidence regarding cardiopulmonary resuscitation among CS athletes.

2.2 Participants A total of 90 (46 females, 44 males) selected recreational athletes CS from public universities in Malaysia participated in this study and voluntarily answered the survey. It should be mentioned that the primary requirements were recreational university athletes aged 18 to 25 years). A snowball method was used in this study. The use of this method allows the survey to detect additional study participants. The inclusion criterion was that the recreational athletes had regular sports training of at least two sessions per week. They participated in handball, football, rugby, taekwondo, basketball and hockey and had to have played contact sports for at least two years. Exclusion criteria were injuries, surgeries, neurological deficits or disabilities within the last six months, and inability to understand Malay or English.

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2.3 Ethical Consideration The ethical considerations in this study, including informed consent, risk of harm, confidentiality and anonymity, and conflict of interest, were explained to participants. The survey was distributed after a university research committee gave permission for the survey to be conducted. An informed consent form was given to each participant assuring confidentiality and anonymity. Respondents were also informed that they could withdraw or refuse to participate in the study at any time without consequence.

2.4 Research Instrument In this study, the KAC questionnaire for CPR adopted from the American Heart Association (AHA Guidelines 2010) (Pei-Chuan Huang et al. 2019; Mbada et al. 2013; Wingen et al. 2018) was used. This questionnaire measured the knowledge, attitude and confidence of CS athletes regarding CPR. In the current survey, data was collected in five sections, including participant consent, demographic information, knowledge, attitude and confidence in CPR using 31 questions. All respondents were required to answer all sections and questions. In addition, a self-report questionnaire using Google Forms (https://forms.gle/hYu 1M1FZH4bYaRWS6) was used in this study. The response options “correct true” or “false” or “do not know” were used to assess knowledge on CPR questions. One mark was awarded for each correct answer to the knowledge questions. “Do not know” answers were treated as incorrect answers and scored zero (Asare 2019). A Likert scale was used to score the questions on attitude and trust. A 5-point scale was used to determine the level of agreement (1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree (neutral), 4 = agree and 5 = strongly agree), likewise a 5-point scale was used to determine the level of confidence (1 = not confident, 2 = less confident, 3 = not really confident, 4 = confident and 5 = very confident). According to the final score, respondents were divided into two categories as at good or at intermediate levels. To pass the American Heart Association’s Advanced CPR (AHA), 80% of the questions in the questionnaire must be answered correctly. Therefore, a score of 80% or more of correct answers answer was considered a good category, while a score below that was an intermediate category (Mersha et al. 2020). A higher score indicates higher self-confidence (Rafiei et al. 2018).

2.5 Data Collection and Analysis The questionnaire assesses KAC on CPR among CS athletes. Data analyses were performed using the IBM Statistical Package for the Social Sciences (SPSS, version

Survey on Knowledge, Attitude and Confidence (KAC) … Table 1 Demographic characteristic of the participant (n = 90)

5

Characteristic

N (%)

Age (years)

22 ± 2 (Mean ± SD)

Gender (M/F)

44 (48.9)/46 (51.1)

Contact sports

Handball 33 (36.7) Football 23 (25.6) Rugby 11 (12.2) Taekwondo 9 (9.9) Basketball 7 (7.8) Hockey 7 (7.8)

24.0) using an independent t test and Pearson correlation. Significance was also set at p < 0.05.

3 Results and Discussion 3.1 Participants Demographics As mentioned earlier, a total of 90 CS athletes participated in this study and completed the questionnaires between May and August 2021. Table 1 shows the demographic data of the participants. The average age of the athletes was 22 (±2) years, with an almost even distribution between male (51%) and female (49%) athletes. Most of them played handball (37%), football (26%) and rugby (12%), and only 7.8% of them were hockey players. Most athletes reported never having a family member with a known cardiovascular disease (88%), and 12.2% reported having someone at risk for cardiovascular disease (CVD) in their family.

3.2 Level of Knowledge, Attitude and Confidence on CPR The results of this study refer to the knowledge, attitude and confidence in CPR by 90 self-answering participants from universities involving CS athletes. The athletes’ knowledge was assessed using 14 validated questions mainly related to the procedure, ratio and process of CPR. The results show that 95.6% of the respondents “have heard of CPR”, but only 44.4% “know how to perform CPR correctly”. The overall scores (by 100) for knowledge level (57), attitude (76) and confidence (64) in CPR are shown in Table 2, indicating that the level was below the ‘good’ category (indicated by score > 80). As the participants of CS were from the fields of health science, sports science, education and engineering (non-medical field), it was likely that the majority of the

6 Table 2 Overall score for level of knowledge, attitude and confidence on CPR (n = 90)

F. F. Zainudin et al. Total score

Mean (±SD)

Knowledge

57.62 ± 27.42

Attitude

76.33 ± 11.47

Confidence

64.18 ± 20.07

participants were not able to perform CPR correctly and their level of knowledge was at an intermediate level and below the “good” category. Furthermore, less than half of them answered the resuscitation procedure correctly—compared to a survey of residents by Chew et al. (2011), where only 78.8% of respondents answered all resuscitation procedures correctly. Obviously, the results are expected to be better for doctors in training, as they have to be certified in Basic Life Support (BSL) and Advanced Cardiovascular Life Support (ACLS) before practicing. In fact, they have to recertify every two years to be able to perform CPR perfectly in their daily work. (Chew et al. 2011). Then, the level of knowledge can improve the individual’s ability to perform effective CPR. In addition, previous studies reported CPR training rates of 41% or more in terms of first responder resuscitation (Pei-Chuan Huang et al. 2019). However, they reported that less than half of the participants (48.9%) attended a CPR course. The main reason for this study finding might be related to the Malaysian education system, where CPR courses are not a compulsory part of the curriculum in either secondary school or university (Mohd Sharif et al. 2018). Similarly, it was also found that Malaysian university students have inadequate knowledge of CPR (Karuthan et al. 2019) and that CPR courses are mainly for medical and health-related majors such as nurses or doctors. This should be changed. However, these findings show that there is a need to change the previous opinion about CPR courses and overcome the stigma that CPR courses should also be offered to athletes, especially those who play high-risk contact sports. In addition, attitudes toward cardiopulmonary resuscitation were assessed using 12 validated questions among the CS athletes. A Likert scale was also used for these questions (1 to 5; strongly disagree to strongly agree). As shown in Table 2, the score for attitude toward CPR was the highest (76.33 ± 11.46). In this context, 58.9% of the respondents stated that they “would perform CPR on a stranger”. However, our results show a higher percentage compared to Pei-Chuan Huang et al. (2019) who evaluated this factor among CPR bystander (Pei-Chuan Huang et al. 2019). However, the results showed that only 44.5% of the respondents reported “wanting to perform mouth-to-mouth ventilation during CPR”. A similar study among medical students at the University of Ethiopia showed that the majority of respondents (63%) were willing to perform chest compressions (CC) and mouth-to-mouth ventilation (MMV), while only 26.3% had no objection and 10.7% of respondents had no objection to performing MMV. For this study, CC plus MMV is unlikely and it occurred mostly in strangers and victims with low trauma, but rather only CC. They reported that 50% of respondents also chose “not to give CPR because they contracted a contagious disease”. The reasons for hesitating to give lay CPR are consistent with the findings

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of previous studies that cited fear of legal problems, harming others or contracting a contagious disease (Pei-Chuan Huang et al. 2019). The results of this study are also consistent with previous studies in which 82.3% of respondents thought that CPR was an opportunity for help. A positive attitude with little knowledge about the CPR procedure may lead to wrong practices instead of saving lives in a dimension that may pose a danger (Mbada et al. 2013). In our study, more than 90% of the respondents agreed that all athletes should attend CPR training. To increase CPR capacity in the population, governments should consider developing appropriate policies. Important details that should be included in public education campaigns and CPR training are that it is acceptable for adult victims of cardiac arrest to have bystanders perform compression-only CPR. Apart from this, the use of CPR and AED is unlikely to result in serious injury, and delays in CPR can cause permanent brain damage to patients in cardiac arrest (Pei-Chuan Huang et al. 2019). It is important to have a positive attitude and sufficient knowledge about CPR to ensure the safety and effectiveness of CPR measures in emergency situations. In addition, the results of the current study showed that 51.1% of the CS athletes were confident in calling an ambulance themselves in the event of cardiac arrest. About 47.7% of the respondents said they had practical skills to check the breathing of a collapsed person in the event of a cardiac arrest. Only 40% of respondents said that they were confident that they had enough knowledge to resuscitate a person in cardiac arrest. To promote the concepts of resuscitation, training programs should focus more on how to develop correct and accurate skills to increase confidence in performing CPR (Pei-Chuan Huang et al. 2019). Not only that, it is important to know that people with lower confidence also lose their knowledge more quickly than people with higher confidence (Abelsson et al. 2020). Apart from it, the selfconfidence is also an essential component of the CPR programmed, as performing CPR on strangers requires a high level of self-confidence to save a life. A person’s motivation to perform CPR is the biggest obstacle that bystanders must overcome, and it depends heavily on their confidence.

3.3 Comparison of Knowledge, Attitude and Confidence on CPR Between Male and Female CS Athletes This study showed that there was no difference in the level of knowledge in CPR between male and female CS athletes. The results showed that both genders had below the “good” category (< 80%). The results of the current study suggest that a structured curriculum post secondary school may be needed to build a better foundation of knowledge and appropriate skills to enable CS athletes to perform effective CPR. At the time of the study, there was no curriculum specifically designed for athlete CPR that included simulation-based assessment. In addition, there was a significant difference between male and female CS athletes in terms of attitude (p = 0.032) and confidence (p = 0.018). Our results illustrate that attitude and confidence in CPR

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Table 3 Comparison of the level of knowledge, attitude and confidence on CPR between male and female CS athletes (n = 90) Variables; total score (0–100)

Male (n = 44) Mean (±SD)

Female (n = 46) t Mean (±SD)

p value

95% CI (lower, upper)

Effect size (d)

Knowledge

59.90 ± 29.11

55.44 ± 25.82

0.771

0.443

−7.051, 15.98

0.162

Attitude

78.98 ± 10.89

73.80 ± 11.54

2.184

0.032

0.46, 9.87 0.462

Confidence

69.27 ± 17.90

59.30 ± 21.00

2.418

0.018

1.77, 18.161

0.511

were higher compared to female athletes (Table 3). In general, KAC score results (mean ± SD) were better for males (K:59.90 ± 29.11, A:78.98 ± 10.89 and C:69.27 ± 17.90) than females (K:55.44 ± 25.82, A:73.80 ± 11.54 and C:59.30 ± 21.00). Nevertheless, the scores for confidence and attitude toward CPR for men are still below the “good” category. In this regard, there are very limited studies available for comparing KAC to CPR among athletes. Further research is needed to assess this condition in a larger sample of athletes participating in contact and high-risk sports. As mentioned earlier, confidence in performing CPR reflects current attitudes as well as knowledge acquired through formal and informal educational programs and previous learning experiences. It has also been suggested that knowledge should be provided through training with high-fidelity simulation (Mohamed et al. 2017) to improve confidence as well. Therefore, future studies need to consider the inclusion of simulation in CPR training as part of the curriculum design for this population.

3.4 The Relationship of the CPR Knowledge Toward the Attitude and Confidence The correlation between the level of knowledge toward attitude (r = 0472) and confidence (r = 0405) in CPR among CS athletes was strongly significant (p < 0.001) (Table 4). The majority of athletes agreed with the importance of learning CPR and believed that adequate knowledge and skills in CPR can help save a life. This study result is also consistent with a previous study that also found a significant relationship, stating that adequate knowledge can lead to a positive attitude and increase selfconfidence (Ihunanya et al. 2020). Therefore, the significant relationship between knowledge and attitude is a necessity to develop good practices and perform CPR correctly in the future. It is worth noting that this study also faced some limitations. First, the time available for data collection was limited to only one month and the sample size was not large. Secondly, the amount of literature on SCA, CPR and the concept of chain of survival is enormous. However, most studies investigating CPR knowledge, attitudes and confidence in CS athletes lack robust objective data and many studies report short

Survey on Knowledge, Attitude and Confidence (KAC) … Table 4 Relationship between the knowledge toward attitude and confidence of CPR among CS athletes

Total score Knowledge of CPR **

9

Attitude

Confidence

r (p value)

r (p value)

0.472(0.001)**

0.405(0.001)**

correlation is p < 0.05 level (2-tailed)

retention intervals after the CPR course. Third, this paper attempts to select the most important representative studies in the field, but other important publications are rightly ignored, especially when there is no restriction to the English version. A larger sample size should be considered in future research to obtain more accurate results. In addition, further studies are needed to investigate the knowledge, attitudes and confidence of coaches and parents regarding CPR in contact sports.

4 Conclusion The results of this study suggest that athletes in contact sports performed below good category on CPR knowledge level, attitude and confidence, although there was a significant relationship between knowledge level and attitude and confidence. While there was no difference between male and female CS athletes in terms of knowledge about CPR, male respondents showed better attitudes and confidence than females. Surprisingly, the majority of the respondents did not know how to perform CPR correctly and they request that CPR training for athletes be considered mandatory. Therefore, it is recommended that future research be conducted with a larger sample that includes both contact and non-contact athletes to confirm the results of the study before designing a specific curriculum for performing CPR with simulation-based assessment. Acknowledgements The authors would like to thank all the participants who took part in the study. We would like to thank the Research Committee and the Research Management and Innovation Centre (RMIC) of Sultan Idris Education University (UPSI) for the methodological development process and publication of the article.

References Abelsson A, Odestrand P, Nygårdh A (2020) To strengthen self-confidence as a step in improving prehospital youth laymen basic life support. BMC Emerg Med 20(1):1–5 Akinremi AA (2014) Knowledge, attitude and perception of sportsmen and personnel about cardiopulmonary resuscitation. Ghana J Physiotherapy 5(1):1–6 Asare YG (2019) Awareness of cardiopulmonary resuscitation (CPR) among university of Ghana students and an assessment of their willingness to practice CPR (Doctoral dissertation, University of Ghana)

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Chandra N, Bastiaenen R, Papadakis M, Sharma S (2013) Sudden cardiac death in young athletes: practical challenges and diagnostic dilemmas. J Am Coll Cardiol 61(10):1027–1040 Chew KS, Hashairi FM, Zarina ZI, Farid AS, Yazid MA, Hisamudddin NA (2011) A survey on the knowledge, attitude and confidence level ofadult cardiopulmonary resuscitation among junior doctors in Hospital Universiti Sains Malaysia and Hospital Raja Perempuan Zainab II, Kota Bharu, Kelantan, Malaysia. Med J Malays 66(1):56–59 Halabchi F, Seif-Barghi T, Mazaheri R (2011) Sudden cardiac death in young athletes; a literature review and special considerations in Asia. Asian J Sports Med 2(1) Ihunanya OM, Oke Michael RN, Babcock BN, Amere LT, RPHN B (2020) Knowledge, attitude and practice of cardiopulmonary resuscitation among nurses in Babcock University Teaching Hospital in Ilishan-Remo, Ogun State, Nigeria. Int J Caring Sci 13(3):1773–1782 Karuthan SR, Firdaus PJ, Angampun AD-A, Chai XJ, Sagan CD, Ramachandran M, Perumal S, Karuthan M, Manikam R, Chinna K (2019) Knowledge of and willingness to perform hands-only cardiopulmonary resuscitation among college students in Malaysia. Medicine 98(51) Mbada CE, Hakeem BO, Adedoyin RA, Awotidebe TO, Okonji AM (2013) Knowledge, attitude and practive of cardiopulmonary resuscitation among Nigerian physiotherapists. J Respir Cardiovasc Phys Ther 2(2):52–62 Mersha AT, Egzi AHKG, Tawuye HY, Endalew NS (2020) Factors associated with knowledge and attitude towards adult cardiopulmonary resuscitation among healthcare professionals at the university of Gondar comprehensive specialized hospital, Northwest Ethiopia: an institutionalbased cross-sectional study. BMJ Open 10(9):e037416 Mohamed FI, Mahmoud FS, Abdel-Salam AA (2017) Effect of high-fidelity simulation training on Pediatric nursing student’s knowledge, practice and attitude regarding cardiopulmonary resuscitation. Egypt J Health Care 8(3):103–113 Mohd Sharif NA, Che Hasan MK, Che Jamaludin FI, Zul Hasymi Firdaus MK (2018) The need for first aid education for adolescents. Enfermería Narayanan K, Bougouin W, Sharifzadehgan A, Waldmann V, Karam N, Marijon E, Jouven X (2017) Sudden cardiac death during sports activities in the general population. Card Electrophysiol Clin 9(4):559–567 Nord A (2017) Bystander CPR: new aspects of CPR training among students and the importance of bystander education level on survival, vol 1580. Linköping University Electronic Press Ozbilgin S, Kuvaki B, Hanci V, Ungur G, Tutuncu O (2016) Awareness and attitudes to cardiopulmonary resuscitation among footballers; a survey in Turkey. Emerg Med (Los Angel) 6(334):2 Pei-Chuan Huang E, Chiang W-C, Hsieh M-J, Wang H-C, Yang C-W, Lu T-C, Wang C-H, Chong K-M, Lin C-H, Kuo C-W, Sun J-T, Lin J-J, Yang M-C, Huei-Ming Ma M (2019) Public knowledge, attitudes and willingness regarding bystander cardiopulmonary resuscitation: a nationwide survey in Taiwan. J Formos Med Assoc 118(2):572–581 Pivaˇc S, Gradišek P, Skela-Saviˇc B (2020) The impact of cardiopulmonary resuscitation (CPR) training on schoolchildren and their CPR knowledge, attitudes toward CPR, and willingness to help others and to perform CPR: mixed methods research design. BMC Public Health 20(1):1–11 Rafiei H, Senmar M, Mostafaie MR, Goli Z, Avanaki SN, Abbasi L, Mafi MH (2018) Self-confidence and attitude of acute care nurses to the presence of family members during resuscitation. Br J Nurs 27(21):1246–1249 Wingen S, Schroeder DC, Ecker H, Steinhauser S, Altin S, Stock S, Lechleuthner A, Hohn A, Böttiger BW (2018) Self-confidence and level of knowledge after cardiopulmonary resuscitation training in 14 to 18-year-old schoolchildren. Eur J Anaesthesiol 35(7):519–526

Influence of Boot Studs on Rugby Players’ Sprinting Performance Sharul Nizam Turiman and Nasrul Hadi Johari

Abstract The player’s sprinting ability is vital in rugby to catch up or avoid being caught by the opponent. The use of appropriate sports boots can improve the player’s sprinting ability. This study investigates the influence of different boot studs on junior rugby players’ 10 m and 20 m sprinting performance. A total of twenty-one rugby players took part in the 10 m and 20 m sprinting test on the natural grass sports pitch. Each player performed the sprinting test using boots with cone and blade stud shapes. Fully automated timing gates were placed at the track 0 m, 10 m, and 20 m mark. Data from the experiments were recorded according to the stud shapes for statistical analysis. The results showed that the players using blade studs with a mean time recorded of 1.50 ± 0.16 s at 10 m and 2.87 ± 0.27 s at 20 m and for cone studs with a mean time recorded of 1.49 ± 0.15 s at 10 m and 2.89 ± 0.28 s at 20 m. The statistical analysis using Cohen’s d revealed trivial qualitative outcome differences in sprinting performance between cone and blade at 10 m with a value of 0.11 and 20 m with the value of 0.14. The analysis showed that players experienced trivial sprinting ability even if they changed their studs from cone to blade. Keywords Boot studs · Rugby · Sprinting

1 Introduction In rugby, sprinting occurs when a player starts a run to catch up and catch an opponent or bring the ball to the try line. Pereira et al. (2018) explained that running is divided into a few categories, whereby each speed for each running category is different; S. N. Turiman · N. H. Johari (B) Faculty of Mechanical and Automotive Engineering Technology, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia e-mail: [email protected] N. H. Johari Centre for Advanced Industrial Technology, Universiti Malaysia Pahang, 26600 Pekan, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_2

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speed for jogging (>1.7 ms−1 ), cruising (>3.3 ms−1 ), striding (>3.9 ms−1 ), highintensity running (>5.0 ms−1 ), and sprinting (>5.5 ms−1 ). A study by (Arrones et al. 2012) showed that in 7 side rugby game, the national rugby players could sprint up to a speed of 5.5 ms−1 and the cumulative distance recorded for sprinting is up to 168 m for men and 181 m for women players. This study proves that rugby players always do fast runs while in a game of rugby. A study by (McLellan and Lovell 2013) found that for a 15-side rugby tournament, a professional rugby player can sprint up to 24 times in a tournament. In a 40 m sprinting test conducted by (Ross et al. 2015), back-position rugby players are capable of sprinting in 5.09 s. Speed on the field is becoming increasingly important in sports; therefore, boots play an important role to athletes. Appropriate boots provide comfort and protect the feet; they also play an important role in helping players to move fast during the game on the field. Iacovelli et al. (2013) claimed that the interaction between the field surface and the surface of sports boots also reduces the risk of injury to a player’s foot. According to the theory by (Winson et al. 2020), the stud on the boot that grips the ground surface will produce high pressure. If the pressure reaches the slip point, the grip between the shoe surface and the ground surface will decrease and cause the player to lose balance and resulting in high injury rate. The greater the traction between the player and the pitch surface, the better the performance of a player. However, if the player does not have enough traction while sprinting, then the player will easily slip and sustain injury (Wannop et al. 2013). In a study conducted by (Ranson et al. 2018), manufacturer needs to consider the interaction between boot shoes and the pitch surface during the design process to produce an optimal boots design. Then, a study conducted by (Dé and James 2014) on seven types of stud shapes using impact hammer equipment showed that each type of stud shape has a different acceleration rate from each other, and the results of (Hennig and Sterzing 2010) study stated that there was a difference of 3% when players ran on a synthetic pitch surface using boot studs of different geometric shapes. Stud characteristics such as the number of studs, measurement of stud length, and distance between studs are important factors influencing player movement. Severn et al. (2011) demonstrated that changes influence friction between the player and pitch surface in the force exerted by the player, distance between studs, and measurements of the stud. The study shows that the design of the stud affects the peak attraction and the amount of movement the player must do to produce maximum resistance during sports. The focus of this study is to investigate the influence of different shapes of boot studs on rugby players sprinting performance. A study by (Driscoll 2012) stated that a range of studded outsoles movement and sprinting performed to measure boots performance and a player’s ability is linked to course time used as an indicator of performance. Later studies such as (Darrall-Jones et al. 2016) and (Pereira et al. 2018) also use time trials to measure the sprinting performance of players. It is hoped that this study can help provide Malaysian rugby players with technical information related to the selection of suitability sports boots for their game style.

Influence of Boot Studs on Rugby Players’ Sprinting Performance Table 1 Anthropometric characteristics and playing experience of the participants

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Variable

Rugby player n = 21

Weight (kg)

69.63 ± 11.56

Height (m)

1.70 ± 0.06

Age (years)

18.13 ± 0.34

Playing experience (years)

2.23 ± 1.11

2 Methodology 2.1 Subject A total of 21 rugby players from Kuantan Vocational College participated in the experiment. All players have undergone rugby training and have experience participating in local rugby tournaments. Players in the range of 18–19 years old are categorized as junior players (Till et al. 2015). The anthropometric characteristics are shown in Table 1. All players were briefed on purpose, benefits, risks, and procedures to be carried out in this experiment, and then, all players signed an informed-consent form before the experiment.

3 Equipment The first step taken by the researcher is to obtain information on boots used by rugby players in Malaysia. A series of questions to gather information on rugby boots usage among the players were compiled in questionnaires. The researcher distributed the online questionnaire through several channels, i.e., over social media, email, and websites, to reach more selected respondents in real time and for quick analysis. Among the targeted respondents are the rugby community at various playing levels, including national professional players, state players, and junior school rugby players. After a week of distributing the questionnaire, the researchers collected 350 responses from the rugby community. As a result of the questionnaire, the researchers found that as many as 77.6% of respondents used boots with a coneshaped stud, 33.1% of respondents used boots with a blade-shaped stud, and only 0.3% of respondents used boots that have a triangular stud. As a result of the analysis conducted on the questionnaire, the researchers decided to use boots with cone-shaped studs and blade-shaped studs (Fig. 1) as the main equipment to be used for sprinting tests since both studs were the most used among rugby players. Boots with triangular-shaped studs were eliminated from the selection due to a low selection percentage from rugby players. Table 2 shows each type of boot used for the sprinting test. Using a stopwatch to record time for sprinting tests is no longer relevant. Jorgensen and Im (2012) stated that the use of manual timing is inaccurate and can cause many

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Fig. 1 Different stud shapes of rugby boots used in sprinting test. (From left to right) conical stud and bladed stud

Table 2 Boots characteristic for acceleration test

Boots model

Stud material

Stud shape

Puma Rapido II

Hard rubber

Cone

Nike Phantom VNM club

Hard rubber

Blade

errors in time readings. Based on the review done in previous studies (Turiman et al., 2022, 2023), it was found that most studies such as from (Seitz et al. 2015) use timing gates equipment in sprinting experiments to record time. This study used the “Photo Finish—Fully Automatic Timing Application” as the timing gate system equipment. The use of Fully Automatic Timing Apps equipment is the most appropriate and accurate method of measuring time for sprinting test (Haugen and Buchheit 2016). This application uses Smart Phone as the primary medium and accurately records the sprint time where the expected error is 0.01 s or less (Lukas and Voigt 2020). A recent article by (Johansen and van den Tillaar 2022) reported that an appropriate phone camera is an excellent alternative to the expensive and complex high-speed camera. It is much cheaper, easy to set up, and has accurate time-measure just like other timing gates. The app connects smartphones via Bluetooth and GPS, and this can prevent the use of wires on the field. Figure 2 shows the picture and time taken by Photo Finish—Fully Automatic Timing Apps.

4 Procedure Before the sprinting test was conducted, the players were provided with two pairs of sports boots: boots with cone studs and sports boots with blade studs. The players wore different boots alternately during rugby training to ensure they got used to both

Influence of Boot Studs on Rugby Players’ Sprinting Performance

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Fig. 2 Picture and time taken by Photo Finish—fully automatic timing apps

types of boots during the sprinting tests conducted later in the day. At the end of the two-week training, an interview program was conducted with the rugby players involved. The interview results showed that the participants were comfortable using both types of boots as long as the boot size was suitable for their feet. A previous study (Sterzing 2015) also states that the comfort of the shoes does not always affect the player’s agility running performance. Player sprinting performance was tested with a 20 m dash. Marker poles with smartphones installed with the Photo Finish application were placed at 0 m, 10 m, and 20 m. The Photo Finish app recorded all participants sprinting data at distances of 10 m and 20 m, respectively. All tests were completed on a natural grass pitch surface in which participants performed three accelerating trials for each type of boot stud. The time was measured to the nearest. Figure 3 shows the sprinting assessment performed by the researchers.

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S. N. Turiman and N. H. Johari Smart phone with Photo Finish apps

Marker pole

10m

Starting point

20m

Fig. 3 Sprinting assessment of rugby players

5 Statistical Analysis All data obtained from the experiments were reported as mean ± standard deviation (SD) after being analyzed using SPSS software. Cohen’s d and 90% confidence limit effect size were used to measure the differences between the players sprinting time. The probability of different values of the effect size is described as a trivial effect: 0–0.19, small effect: 0.2–0.59, and moderate effect: 0.6–0.79 (Cohen 1988).

6 Result and Discussion Based on the experiments conducted, the average 10 m and 20 m sprinting performance for a boot with cone stud and blade stud was recorded in Table 3. The results showed that the sprinting performance of the player at 10 m using the cone stud boot was 1.49 ± 0.15 s and the blade stud boot was 1.50 ± 0.16 s. While the sprinting performance of the player at 20 m using a cone stud boot was 2.89 ± 0.28 s, the blade stud boot was 2.87 ± 0.27 s. Based on the data obtained, the researchers performed an analysis using Cohen’s d method (Cohen 1988) to identify the most suitable type of boot stud used for player sprinting. The formula for Cohen’s d is as follows: Table 3 Time record against 10 m and 20 m sprinting performance with different stud types

Stud type (Mean ± SD) Cone stud

Blade stud

10 m sprinting time (s)

1.49 ± 0.15

1.50 ± 0.16

20 m sprinting time (s)

2.89 ± 0.28

2.87 ± 0.27

SD = Standard Deviation

Influence of Boot Studs on Rugby Players’ Sprinting Performance

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where M E and M C are the mean of groups 1 and 2, respectively, and N is the sample size. The comparison between the cone stud and blade stud for 10 m sprinting in Table 4 showed a trivial result of 0.11, and the comparison between the cone stud and blade stud for 20 m sprinting also showed a trivial result of 0.14. Sprinting performance difference between cone stud and blade stud can also be seen through the descriptive plot in Fig. 5. The experiment results show that rugby players sprint moderately faster by wearing boots with cone studs compared to blade studs at 10 m. However, the players are slightly faster with blade studs compared to cone studs at 20 m based on recorded time for both distances. Nevertheless, the analysis performed through Cohen’s d method found that the difference in player sprinting performance at 10 m and 20 m distances was trivial. These data show no significant difference if a rugby player uses a boot with a cone or blade-type stud while performing sprinting activities. The shape of the stud plays a role in the penetration of the stud into the ground during sprinting. A hard pitch surface makes it difficult for the stud to penetrate the ground, and the effect of reduced stud penetration will reduce the friction of the boot surface against the pitch surface (Caple 2011). The use of boots with cone Table 4 Sprinting performance difference between stud types based on Cohen’s d

Cone vs blade

Cohen’s d (90% CI)

Qualitative outcome

10 m sprinting

−0.11 (−0.47 to 0.26)

Trivial

20 m sprinting

0.14 (−0.22 to −0.5)

Trivial

CI = Confidence Interval

Fig. 5 Descriptive plot of sprinting performance between a cone and blade studs at 10 m, b cone and blade studs at 20 m

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and blade studs in this experiment shows that different studs’ shapes could affect the traction, resulting in different penetration capabilities to the ground. A similar finding was also recorded by (Barry and Milburn 2013). Studies related to cone stud by (Thomson et al. 2019) have shown that cone studs have the highest peak rotational traction compared to other types of studs. Later, (Blanchard and Behr 2020) reported that cone stud shape influences better rugby player running movement assessment outcomes. Studies related to bladed studs by (Sterzing 2015) stated that blade-shaped studs have a larger obstructive area for efficient deceleration and acceleration forces while running. Before that, (Müller et al. 2010) studies reported that blade-shaped stud geometry is designed for firm ground surfaces. However, in-depth studies need to be done on the effectiveness of this bladed stud against other surfaces, such as soft surfaces or synthetic pitch surfaces. On the other hand, (Grund and Senner 2010) claimed the use of stud blades is not recommended, based on the tests using a pneumatic test device that showed that the boot with blade shape stud produced the lowest values for peak and effective torque, which caused the player to easily slip due to lack of resistance to the pitch surface. The study test was supported by (Driscoll 2012) and (Mansfield and Bucinell 2016) that the use of sports boots with blade studs will cause players to be easy to get injured in the game than other types of studs.

7 Conclusion Several researchers have studied the sprinting abilities of rugby players from various angles point of interest. The articles prove that the players’ speed is an important asset to the rugby team. Therefore, studies related to rugby sports equipment, such as sports boots, must also align with the players’ abilities. This study was conducted to identify the most suitable studs to be used in order to improve the sprinting ability of rugby players. Analysis using Cohen’s d showed no significant difference in the player’s sprinting performance using a boot with a cone or blade-type stud. It is hoped that future researchers will conduct more studies on the effect of boot studs on players’ performance on various pitch surfaces. Acknowledgements The authors would like to thank the management of Kuantan Vocational College for providing facilities and the rugby players, and to Universiti Malaysia Pahang for financial assistance under grant no. PGRS210345.

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Seitz LB, Barr M, Haff GG (2015) Effects of sprint training with or without ball carry in elite rugby players. Int J Sports Physiol Perform 10(6):761–766. https://doi.org/10.1123/ijspp.2014-0193 Severn KA, Fleming PR, Clarke JD, Carre MJ (2011) Science of synthetic turf surfaces: investigating traction behaviour. Proc Inst Mech Eng, Part P: J Sports Eng Technol 225(3):147–158. https:// doi.org/10.1177/1754337111408980 Sterzing T (2015) Athletic footwear research: effects of shoe construction and relationships of evaluation parameters. November Thomson A, Whiteley R, Wilson M, Bleakley C (2019) Six different football shoes, one playing surface and the weather; assessing variation in shoe-surface traction over one season of elite football. PLoS ONE 14:4, e0216364. https://doi.org/10.1371/journal.pone.0216364; PLoS ONE 14(6):1–13. https://doi.org/10.1371/journal.pone.0218865 Till K, Jones B, Darrall-Jones J, Emmonds S, Cooke C (2015) Longitudinal development of anthropometric and physical characteristics within academy rugby league players. J Strength Cond Res 29(6):1713–1722 Turiman SH, Ahmad Z, Johari NH (2023) Preliminary study on the influence of boot studs on Rugby players’ sprinting performance. Lect Notes Electr Eng 882:61–71. https://doi.org/10.1007/978981-19-1577-2_6 Turiman SN, Ahmad Z, Johari NH (2022) Sprint performance in Rugby players: a systematic review. Lect Notes Mech Eng 253–266 https://doi.org/10.1007/978-981-16-4115-2_20 Wannop JW, Luo G, Stefanyshyn DJ (2013) Footwear traction and lower extremity noncontact injury. Med Sci Sports Exerc 45(11):2137–2143. https://doi.org/10.1249/MSS.0b013e318299 ac56 Winson DMG, Miller DLH, Winson IG (2020) Foot injuries, playing surface and shoe design: should we be thinking more about injury prevention. Foot Ankle Surg 26(6):597–600. https:// doi.org/10.1016/j.fas.2019.07.013

Influence of Receiver’s Position on Short-Serve Placement Among Double Badminton Players Allan Ivan Mauming and Raihana Sharir

Abstract The presence of an opponent or receiver was assumed to alter the serve trajectory of a player considerably. In some sports, players tend to serve the ball to the larger area of the court, and some tend to serve away from the receiver’s body; however, the change of the receiver’s position and its influence on decisionmaking was not analytically studied. Therefore, this study investigates the influence of the receiver’s different positions on the placement of short serve among badminton double players. Skilled badminton players (N = 15) with a minimum of three years of consecutive training in double discipline participated in this study. Participants were required to perform 30 short serves with the presence of a receiver at two different positions. Video recording was used to record the shuttlecock placement. McNemar’s test revealed that even though Area A has a more frequent short serve made by the players compared to Area B, there were no significant differences in short-serve placement between Area A and Area B, p = 0.385. However, based on the Chi-square test showed that there was a significant association between the receiver’s position and short-serve placement (X2 (1) = 116.2, p < 0.001). Findings showed that players preferred to serve away from the receiver’s body, demonstrating that the amount of attention focused was directed away from the receiver and to the larger space. Hence, a skilled badminton player’s short-serve placement selection was influenced by the presence and different positions of the receiver on the court. Keywords Badminton · Short serve · Decision making · Serve placement · Racket sport · Racquet sport

A. I. Mauming · R. Sharir (B) Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia e-mail: [email protected] R. Sharir Sports and Exercise Biomechanics Special Interest Group, Faculty of Sport Science and Recreation, Universiti Teknologi MARA, Shah Alam, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_3

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1 Introduction Badminton is one of the most popular sports in the world, with 200 million enthusiasts (Kwan et al. 2010). Badminton is the quickest of the so-called racquet sports and is considered one of the three most challenging sports in terms of physical demands. This is due to the complexity of coordination sports, which features the speed of movement, thinking, and technique execution (Bekiari et al. 2015). Plus, it is known as the fastest sport in the world with its high pace and dynamic, energetic rallies (Butterworth et al. 2012). Subsequently, the accuracy of projecting the shuttlecock is also essential to success, not only in badminton but other sports that involve projecting an object rapidly toward a target location, such as football, archery, and tennis (Vial et al. 2019). Launching the shuttlecock to a specific point in space or area has consequently been a critical factor for performance (Duncan et al. 2017; Jardine and Martin 1983) and has been deemed a skill to master. A service stroke signifies the starting point of a dynamic interaction between the player and opponent that could disrupt the receiver’s balance or create a disadvantage for the server during the rally (Gómez et al. 2017). Hence, mastering the more advantageous service stroke selection is preferred. According to Yao and Liang (2020), mid-court is where the highest scoring area was observed (46.7%), followed by backcourt (30.5%) and lastly, frontcourt (22.8%). Therefore, it is a drawback for a server to perform a high serve due to the high percentage of scoring a score by the opponent. To minimize the percentage of the opponent’s scoring a score, it is beneficial for the server to utilize a short serve because it is a skill in which the shuttlecock typically travels very close to the net and drops directly as it passes over the net. Studies have shown that a short serve is more frequently used than a deep serve as it gives an advantage to the player whether they want to be in an attack position or defend themselves from being attacked by the opponent (Pérez-Turpin et al. 2020; Singh et al. 2016). The short serve in badminton should focus on the accuracy of the landing point and the trajectory of the shuttlecock when an opponent is present (Vial et al. 2020). Previous studies suggest that the actual on-court positioning of the opponent may influence the shot selection and projectile’s trajectory (Loffing and Hageman 2014; McGarry and Franks 1995). For example, in the football penalty, the goal-side selection was influenced by the more prominent space side, even when the goalkeeper was standing precisely in the center of the goalpost (Pereira 2019). While in volleyball, the server is likely to choose a large area to serve even if there is a slight displacement of the receiver (Noël et al. 2016), and in tennis, the server projected the ball 5.88° further from the returner (Whiteside and Reid 2016). Thus, a larger space side is considered in most sports when deciding on serve placement. Therefore, the opponent’s position in influencing the athlete’s decision-making is essential and warrants further observation. When aiming for a specific target, the target’s (opponent) physical location affects the trajectory chosen by the person projecting the object (Chow et al. 2008). This means that the player obtains an informational constraint that only influences their

Influence of Receiver’s Position on Short-Serve Placement Among …

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action. Though the prediction model by Vial et al. (2020) found that with the presence of an opponent, the shuttlecock trajectory was not only focused on one area but was spread along the frontline and was considered an inaccurate serve. The serve placement prediction was spread, which means that the shuttlecock placement did not have a fixed landing when there was the presence of an opponent. So, do skilled badminton players still apply accurate shuttlecock trajectories based on shuttlecock placement when an opponent is present or whether they alter their approach despite preserving the intention of hitting a particular placement location or target regardless of the presence of an opponent? In simpler terms, what is the deciding factor of one’s short-serve placement selection? As none has observed the opponent’s position (receiver), in the game of badminton, especially during serving, it brings us to the aim of this study, which is to investigate the influence of the receiver’s different positions on the placement of short-serve among badminton double players.

2 Methods Upon ethical approval of the Universiti Teknologi MARA’s Research Ethics Committee, recruitment of skilled male double badminton players (n = 15) aged between 18 and 35 years old who were free from injuries within the past 12 months before testing was done [age (24.6 years ± 0.83), height (172.73 cm ± 6.45), weight (70.67 kg ± 6.82)]. Skilled players were from the Sabah Badminton Association player’s list and had been consecutively training for the past 3 years and had competitive experience in national and university tournaments. Par-Q form, injury history questionnaire and information sheet were given to the participants before the testing. Procedures and protocols were explained to each participant prior to testing.

2.1 Instrument A video camera from a mobile phone (Samsung Galaxy A7) was used to record the shuttlecock placement placed behind the server. The position of the video camera was adjusted to include the view of the whole court and both the server and receiver. The badminton court size and net height were set up in accordance with the Badminton World Federation (BWF) standards. Once the serving and receiving participants were in their respective position, video recording was started to record the first successful trial until the end of the 30th trial of short serve.

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Fig. 1 Placement of short serve

2.1.1

Placement of Short Serve (Server)

There are only two expected placements where the shuttlecock will land (Area A and Area B). This is the typical shuttlecock landing placement for a short serve. It will either be in Areas A or B (Zhang et al. 2013) (Fig. 1).

2.1.2

Receiver’s Position

Two different receiver positions were included in this study. Position 1 is when the receiver is close to the T-line of the court or center of the court (Fig. 2) while Position 2 is when the receiver is away from the center court (Fig. 3). Each of the positions was randomly sequenced for the 30 short-serve trials (fifteen times for each position).

Fig. 2 Receiver’s position 1

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25

Fig. 3 Receiver’s position 2

2.2 Procedure Prior to testing, participants performed 10 min of dynamic warm-up to prevent any risk of injury. Afterward, the server and receiver were asked to position themselves in the court. The receiver randomly stands on one of the two positions while the server positioned themselves at their common serve area during a competition match. When both receiver and server are ready, the server performed the short serve with selfselected trajectory at the frontcourt (serve area). The receiver was allowed to return the serve to mimic the competition environment; however, the server does not need to return the rally. The server must perform 30 short serves trials with two different receiver positions. In addition to video recording, the researcher also did a notational observation of the short-serve placement made by the server for each trial. After the server had finished its 30th short-serve trial, both the server and receiver did their cooling down session.

3 Results All data were collected and analyzed in the Statistical Packages for Social Sciences (SPSS) version 26. Descriptive analysis of individual characteristics was age, height, and weight. McNemar’s test was used to observe the differences in short-serve placement between the receiver’s position 1 and position 2, while the Chi-square test was used to identify the association between the receiver’s position and short-serve placement. The significant level was set at p < 0.05.

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A. I. Mauming and R. Sharir

Table 1 Receiver’s position and short-serve placement crosstabulation

Area A

Area B

Total

Position 1

64

161

225

Position 2

178

47

225

Total

242

208

450

Table 2 Differences of short-serve placement

Value McNemar’s test No. of valid cases

Exact Sig. (2-sided) 0.385

450

a. Binomial distribution used

3.1 Differences of Short-Serve Placement The receiver’s position and short-serve placement crosstabulation table describes the total of short serve made in Area A (242 serves) and Area B (208 serves). Based on the crosstabulation table, Area B has more frequency of short-serve placement than Area A when the receiver was in Position 1 while Area A was frequently served when the receiver was in Position 2 (Table 1). McNemar’s test found no significant differences in short-serve placement, p = 0.385 (p > 0.05). Area A has more frequent short serve made by the players compared to Area B; however, there were no significant differences in short-serve placement seen between Area A and Area B (Table 2).

3.1.1

Association Between Receiver’s Position and Short-Serve Placement

The Chi-square test of independence showed that there was a significant association between the receiver’s position and short-serve placement (X 2 (1) = 116.2, p < 0.001) (Table 3). Table 3 Association between receiver’s position and short-serve placement Value

df

Asymptotic significance (2-sided)

Pearson Chi-square

116.183

1

0.000

No. of valid cases

450

Exact Sig. (2-sided)

Exact Sig. (1-sided)

a. 0 cells (0.0%) have expected count less than 5. The minimum expected is 104.00 b. Computed only for 2 × 2 table

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27

4 Discussion The aim of this present study was to investigate the influence of the receiver’s different positions on the placement of short serve among badminton double players. As both trajectory angle and serve placement is of importance, observing how the presence of an opponent can influence the decision-making of serve placements may provide information and understanding of serving strategies to the players and coaches in planning their tactical moves during gameplay and training. Ideally, an accurate short serve is made when the apex of the shuttlecock trajectory is just before the net, so as it travels over the net, the shuttlecock is at a low height. Then, the placement of the shuttlecock is at the middle front of the serve square (near the T-line) (Edwards et al. 2007). Then again, the server tends to change its strategy when there is a presence of an opponent or receiver. As Vial et al. (2020) found in their study, the short-serve placement made by the player was spread all over the frontline court with the presence of a receiver and it was suggested that the position of the receiver could be the other factor of short-serve trajectory variation. Based on the results of this study, there were no significant differences in the short-serve placement frequencies observed between Area A and Area B when the receiver stands in a different position. Participants in this study used both areas to place the shuttlecock depending on the receiver’s position. This finding was aligned with a previous study where elite squash player’s shot responses were found to be determined by the location of the opponent on the court (Vuˇckovi´c et al. 2013). Noël et al. (2016) also observed this in volleyball athletes who are likely to serve in the largest area on the opponent’s court. The same goes for football during the penalty kick, the goal selection is influenced by where the goalkeeper is standing, and they are likely to kick at the wider side even though the goalkeeper is standing exactly at the center of the goalpost (Pereira 2019). The Chi-square test revealed an association between the receiver’s position on the court and the short-serve placement selected by the server. This finding can be supported by a previous study on basketball where different ball shot trajectory was made by the player when there was the presence of a defender (Rojas et al. 2000). Similar findings by Pinder et al. (2011) also show the association of players altering their movements in response to information provided by the opposing player. This is related to the athlete-environment interaction where the performance or decisionmaking of the athlete is influenced by their surrounding (i.e., opponent) (Hettinga et al. 2017). During a match-play, the opponent (receiver) will often try to jump forward to the net to attack and smash the shuttlecock at the highest point of the shuttlecock flight (Pinder et al. 2011). Thus, to reduce the advantage of the receiver, choosing a different trajectory of the short serve could be a good idea. Therefore, it is important for players to consider observing the receiver for cues in sudden movements. Regarding finding cues, the visual search of a skilled player was found to be greater than a less skilled player (Chia et al. 2017). Compared to less skilled players, it was found that a greater number of fixations with more visual location search was made by the skilled players to gain information on cues and minimize the chance of a successful attack made by the opponent. Instead of depending on

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A. I. Mauming and R. Sharir

landing location (which seldom occurs in matches and is often short of the line), it is recommended to evaluate services based on apex location and height above the net. This strategy reflects match conditions, and training to meet these standards resembles a match setting. Professional players focused on the quality of their short-serve technique rather than looking at the opponent’s position for cues, or we could say less risky serve to lead the point (Chow et al. 2014). Performing accurate short serve was suggested as it can be difficult for the opponent to do an attacking (Vial et al. 2019). Another reason to focus on the quality of performing short serve may help to avoid the strategic counter-responses made by the opponent where they try to lure the serving player to serve at a particular target area. This strategic decision-making is well studied in soccer penalty kicks (Chiappori et al. 2002; Palacios-Huerta 2003), and it could exist in badminton as well. Thus, this idea could be a trick or trap made by the opponent to increase the possibility of attacking first. Contrary to other studies which focused on the opponent’s position as a cue before they execute their shot or serve (Vuˇckovi´c et al. 2013; Pereira 2019; Whiteside and Reid 2016). Overall, the receiver’s position is considered when the server decides where to place their short serve.

5 Conclusion In conclusion, the present study revealed that both receiver’s positions influenced the player’s short-serve placement selection among skilled badminton double players. Players were likely to serve away from the receiver’s body and aim for a larger area to place their serve. Future research should examine stance and anthropometric profile as well as spotting opponent cues as it may further assist players in the decision-making of the short-serve placement.

References Bekiari A, Perkos S, Gerodimos V (2015) Verbal aggression in basketball: perceived coach use and athlete intrinsic and extrinsic motivation. J Phys Educ Sport 15(1):96–102. https://doi.org/10. 7752/jpes.2015.01016 Butterworth DA, Turner JD, Johnstone AJ (2012) Coaches perceptions of the potential use of performance analysis in badminton. J Perform Anal Sport 12:17. https://doi.org/10.1080/247 48668.2012.11868610 Chia JS, Burns SF, Barrett LA, Chow JY (2017) Increased complexities in visual search behavior in skilled players for a self-paced aiming task. Frontiers Psychol 8. https://doi.org/10.3389/fpsyg. 2017.00987 Chiappori P-A, Levitt S, Groseclose T (2002) Testing mixed-strategy equilibria when players are heterogeneous: the case of penalty kicks in soccer. Am Econ Rev 92(4):1138–1151. https://doi. org/10.1257/00028280260344678 Chow JY, Davids K, Button C, Rein R (2008) Dynamics of movement patterning in learning a discrete multiarticular action. Mot Control 12(3):219–240

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Chow JY, Seifert L, Hérault R, Chia SJY, Lee MCY (2014) A dynamical system perspective to understanding badminton singles game play. Hum Mov Sci 33:70–84. https://doi.org/10.1016/ j.humov.2013.07.016 Duncan MJ, Chan CK, Clarke ND, Cox M, Smith M (2017) The effect of badminton-specific exercise on badminton short-serve performance in competition and practice climates. Eur J Sport Sci 17(2):119–126 Edwards B, Waterhouse J, Atkinson G, Reilly T (2007) Effects of time of day and distance upon accuracy and consistency of throwing darts. J Sports Sci 25(13):1531–1538. https://doi.org/10. 1080/02640410701244975 Gómez M-Á, Ruiz-Pérez L-M, Cid A, Rivas F, Sampaio J (2017) Serve is not an advantage in elite men’s badminton. Complex systems in sport, international congress linking theory and practice 4 Hettinga FJ, Konings MJ, Pepping GJ (2017) The science of racing against opponents: affordance competition and the regulation of exercise intensity in head-to-head competition. Front Physiol 8:118. https://doi.org/10.3389/fphys.2017.00118 Jardine R, Martin NG (1983) Spatial ability and throwing accuracy. Behav Genet 13(4):331–340 Kwan M, Tang W-T, Cheng C-L, Rasmussen J (2010) Measurement of badminton racket deflection during a stroke. Int Sports Eng Assoc 12:12. https://doi.org/10.1007/s12283-010-0040-5 Loffing F, Hagemann N (2014) On-court position influences skilled tennis players anticipation of shot outcome. J Sport Exerc Psychol 36(1) McGarry T, Franks IM (1995) Modeling competitive squash performance from quantitative analysis. Hum Perform 8(2):113–129 Noël B, Hüttermann S, Kamp JVD, Memmert D (2016) Courting on the beach: how team position implicitly influences decision-making in beach volleyball serves. J Cogn Psychol 28(7):868–876. https://doi.org/10.1080/20445911.2016.1194847 Palacios-Huerta I (2003) Professionals play minimax. Rev Econ Stud 70(2):395–415 Pereira MRDJ (2019) Goal-side selection of penalty shots in soccer. Spring, 24 Pérez-Turpin JA, Elvira-Aranda C, Cabello-Manrique D, Gomis-Gomis MJ, Suárez-Llorca C, Andreu-Cabrera E (2020) Notational comparison analysis of outdoor badminton men’s single and double matches. J Hum Kinet 71:7. https://doi.org/10.2478/hukin-2019-0121 Pinder RA, Davids K, Renshaw I et al (2011) Manipulating informational constraints shapes movement reorganization in interceptive actions. Atten Percept Psychophys 73:1242–1254. https:// doi.org/10.3758/s13414-011-0102-1 Rojas FJ, Cepero M, Ona A et al (2000) Kinematic adjustments in the basketball jump shot against an opponent. Ergonomics 43:1651–1660 Singh DOJ, Thapa SK, Baro DM, Gogoi DD (2016) The effect of game specific training on selected badminton skills. Int J Appl Res 2:4. https://doi.org/10.13140/RG.2.2.18020.78721 Vial S, Cochrane J, Blazevich AJ, Croft JL (2019) Using the trajectory of the shuttlecock as a measure of performance accuracy in the badminton short serve. Int J Sports Sci Coach 14:6. https://doi.org/10.1177/1747954118812662 Vial S, Croft JL, Schroeder RT, Blazevich AJ, Wilkie JC (2020) Does the presence of an opponent affect object projection accuracy in elite athlete?. Int J Sports Sci Coach 6 https://doi.org/10. 1177/1747954120915670 Vuˇckovi´c G, James N, Hughes M, Murray S, Sporiš G, Perš J (2013) The effect of court location and available time on the tactical shot selection of elite squash players. J Sports Sci Med 12(1):66 Whiteside D, Reid M (2016) Spatial characteristics of professional tennis serves with implications for serving aces: a machine learning approach. J Sports Sci 7 https://doi.org/10.1080/02640414. 2016.1183805 Yao B, Liang N (2020) Research on position optimization of badminton doubles based on wireless sensor and human-computer interactive training. Research square, p. 16 Zhang B, Li F, Jiang W (2013) Mixed doubles match technical and tactical analysis of world badminton champion based on mathematical statistics. Ad Phys Educ 03(04):154–157. https:// doi.org/10.4236/ape.2013.34025

Effect of Kinesiology Tape Application on Shoulder Pain and Mobility Among State-Level Badminton Players Radin Rafeeuddin Radin Dzulfakar, Fariha Sofiya Mohd Shufaian, and Raihana Sharir

Abstract Due to the highly repetitive and complex overhead movements of the shoulder during match-play or training, shoulder pain is common among badminton players. Although kinesiology tape (KT) application has become popular and is widely used in sports, its effectiveness remains contradicting as its efficacy could be psychological. Therefore, the study attempted to determine the effect of applying KT on shoulder pain reduction and mobility improvement among state-level badminton players. Fifteen male badminton players who represented Majlis Sukan Negeri Kedah SUKMA 2021 participated in this study. All participants completed the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire and three movements from the Selective Functional Movement Assessment (SFMA) before KT application prior to training. The Y-strip technique was applied on each participant’s deltoid. Both DASH and SFMA were repeated 45 min after badminton training. Paired-sample t tests revealed significant differences between pre- and post-tests DASH scores (p < 0.05 **please give exact p value) as well as both Upper Extremity Pattern 1 (p = 0.0001) and Upper Extremity Pattern 2 (p = 0.0004) from the SFMA, though not for the Overhead Deep Squat (p = 0.164). Overall, for the participants in this study, KT has an effect on shoulder pain and mobility scores in state-level badminton players. Keywords Kinesiology tape (KT) · Shoulder pain · Shoulder mobility · SFMA · Dash questionnaire

R. R. R. Dzulfakar · F. S. M. Shufaian · R. Sharir (B) Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Shah Alam, Malaysia e-mail: [email protected] R. R. R. Dzulfakar · R. Sharir Sports and Exercise Biomechanics Special Interest Group, Faculty of Sport Science and Recreation, Universiti Teknologi MARA, Shah Alam, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_4

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R. R. R. Dzulfakar et al.

1 Introduction Although badminton has been generally acknowledged as a safe sport, injury is inevitable. Studihes have found that for every 1000 h of play, there would be a 1.6– 2.9% increased risk of injuries in badminton (Hensley and Paup 1979; Jørgensen and Winge 1987). Shoulder pain in badminton players is a very common and troubling issue. As the shoulder region is utilized during highly repetitive and complex overhead movements (i.e., with the shoulder in abduction or external rotation) during badminton match-play or training, resultant painful conditions may affect a player’s performance (Phomsoupha and Laffaye 2020). The anterior instability of the shoulder joint may cause impingement of the rotator cuff leading to the overall shoulder pain (Ticker et al. 1995) but 17–28% of badminton players playing with an ongoing injury to the shoulder (Arora et al. 2015). Several studies have observed that injuries and pain to the shoulder do not inhibit the players from playing, though it will affect the quality of their match-play (Arora et al. 2015; Fahlström and Söderman 2007; Yung et al. 2007). Despite the known occurrence of shoulder pain, there is scarcity of information concerning the best methods of treatment and prevention (Butler et al. 2015). For other overhead sports in which shoulder pain is an issue, i.e., swimming, when the pain or injury gets too intense, pain medication was used to manage the pain (Hibberd and Myers 2013). Typical treatment recommendations would include taping, low-power laser, dry-needling, flexibility exercises, resistance, and neuromuscular training of the upper limb (Ansari et al. 2022; McClure et al. 2012). Whichever treatment is done, the ultimate interest would be to reduce pain and improve mobility and function. Though previous studies have shown that a less invasive treatment would be favorable, it is easier to administer (Brox et al. 1999, 1993). A non-invasive physiotherapeutic approach such as the Kinesiology Tape (KT) has started to become more popular in recent years and has been widely used in the sporting industry. KT was designed to mimic the qualities of the human skin and is used to stabilize and aid muscles and joints without constraining the range of motion (Kalron and Bar-Sela 2013). Upon application of KT on the targeted area, it recoils and produces a pulling force that serves as the main stabilizer for the targeted area. Therefore, KT is used for a variety of purposes, including improving blood flow (Woodward et al. 2015), reducing discomfort (Lee et al. 2016), and increasing flexibility (Farquharson and Greig 2015). KT has also been used for managing various musculoskeletal disorders including shoulder pain (Kalron and Bar-Sela 2013). Limited literature provides solid evidence on the role of KT in treating shoulder pain (Ghozy et al. 2020). According to Lee (2015), correct application of KT adhering to the taping method is considered to be associated with its efficacy; therefore, appropriate technique and knowledge of the practitioner to ensure correct application are warrant. Observing the duration of tape applied is also of importance as KT is usually worn for several days before taking off. However, Montalvo et al. (2014) found that KT does not help in healing or relieving discomfort after musculoskeletal injury. Even though findings from previous studies on the

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effectiveness of KT are varied and contradicting, and despite the uncertainty, usage and user satisfaction of KT remain high implying that its use may have a psychological component (Reneker et al. 2018). Therefore, the study aims to determine the effect of applying kinesiology tape on shoulder pain and mobility among SUKMA Kedah badminton players.

2 Methods 2.1 Participants 15 male badminton players (mean ± SD age: 22.59 ± 4.8 years; stature: 181.7 ± 6.3 cm; mass: 78.4 ± 8.3 kg) volunteered to participate in this repeated-measures study. All participants were active badminton players from the Kedah National Sport Council (MSN) who have participated in regional and national championships across Malaysia and are currently participating in full-team training for Sukan Malaysia (SUKMA). Participants were given a questionnaire on their injury history, and none had a recent (< 12 months) major injury. Written consent was obtained from all the participants, and the study was performed in accordance with the UiTM Research Ethics Committee guidelines [(REC/11/2021 (UG/MR/919)].

2.2 Shoulder Pain To assess pain and discomfort in the shoulder joints, a Disability of the Arm, Shoulder and Hand (DASH) Questionnaire was used. DASH is a self-administered questionnaire for the evaluation of impairment and symptoms in the upper extremity. It consists of a 30-point item scale of disability or symptom that relates to the ability to which specific tasks, the severity of pain symptoms, the impact on social activities, and daily routines that are deemed challenging. The DASH questionnaire has been used widely in the context of pain relating to the shoulder joint during daily activity and overall performance (Hanson et al. 2019; Harrington et al. 2014; Roe et al. 2013; Roy et al. 2009; Gabel et al. 2006; Beaton et al. 2001). The calculation of the results is based on the DASH instructions on 30 questions of continuous scale (Institute for Work and Health, Toronto, Ontario, Canada).

2.3 Shoulder Mobility Three (3) Selected Functional Movement Assessment (SFMA) (Cook 2010) were used to observe shoulder mobility and range of motion, i.e., Upper Extremity Pattern

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R. R. R. Dzulfakar et al.

Fig. 1 a Upper extremity pattern 1-medial rotation extension, b Upper extremity pattern 2-lateral rotation flexion, c Overhead deep squat (image source Glaws et al. 2014)

1 (MRE), Upper Extremity Pattern 2 (LRF), and Overhead Deep Squat (ODS). These movements assessed the shoulder in a single plane and were evaluated by the investigator and closely monitored by a certified physiotherapist. The SMFA evaluates the shoulder range of motion by measuring functionally nonpainful (FN), functionally painful dysfunctions (FP), dysfunctional nonpainful, and nonpainful dysfunctions. Specifically for this study as all of the participants are currently active badminton players with no upper limb dysfunctions, only FN and FP were evaluated (Fig. 1).

2.4 Kinesiology Tape (KT) Mapping on the Shoulder The Y-strip technique was applied on the participants representative of the supraspinatus as its insertion to the origin with the tape directly on the skin’s surface. The ‘strip’ refers to the central section of the tape, which then produces the two tails resembling the letter ‘Y’ (Fig. 2). The general application guidelines were consistent with the protocol for rotator cuff tendonitis/impingement suggested by Kase et al. (2003). The Y-strip representative of the deltoid is also applied from insertion to origin with paper-off tension. It was applied with the first tail to the anterior deltoid while the arm was externally rotated and horizontally abducted. The tail for the posterior deltoid was applied with the arm horizontally adducted and internally rotated as if reaching to the outside of the contralateral hip. Taping was administered by the same investigator for all 15 participants to ensure reliability and validity of testing. Prior to the test, a pilot work was done where the investigator would place the Y-strip technique following the guidelines (Kase et al. 2003) on pilot participants and was observed by a certified physiotherapist in MSN Kedah until satisfactory.

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Fig. 2 Y-strip technique application. (image source https://www.acefitness.org/)

2.5 Procedure Participants completed the DASH questionnaire followed by the three SMFA. Subsequently, KT was applied to the participant’s shoulder. After 45 min of training, participants filled up another DASH questionnaire and performed the SMFA after removal of tape. During the 45-min wear period, the participants resumed their usual badminton training.

2.6 Statistical Analysis Descriptive statistics were used to determine the mean and standard deviation of the demographic data, i.e., age, height, mass, and hand dominance (referred to as the hand that holds the racquet). Inferential statistics were determined using Statistical Package for Social Science (SPSS) Statistics 20.0 Software. Paired-sample t test was used to compare the mean value of differences of the effect of kinesiology tape application on shoulder pain and mobility of the badminton players. Significance level was set at p < 0.05.

3 Results Table 1 summarizes the results for the two different measures to observe the KT application effect (mean ± SD). A paired sample t test was run on a sample of 15 male badminton players to determine whether there was a statistically significant mean of difference between pre- and post-45-min effect of applying kinesiology tape on shoulder pain and mobility. Shoulder pain was assessed through the DASH questionnaire while shoulder mobility was evaluated through 3 SFMA movements

36 Table 1 Results for pre- and post-45 min of KT application ± SD

R. R. R. Dzulfakar et al. (N = 15)

Pre

Post-45

DASH (0–100)

7 ± 15.357

3.055 ± 2.347

Upper extremity pattern 1

1.666 ± 0.238

1±0

Upper extremity pattern 2

1.6 ± 0.257

1±0

Overhead deep squat

1.133 ± 0.123

1±0

SFMA (1 = FN, 2 = FP)

DASH Disability of the Arm, Shoulder and Hand; KT kinesiology taping; SFMA Selected Functional Movement Assessment; FN Functionally Nonpainful; FP Functionally Painful; SD standard deviation

with either Functionally Nonpainful or Functionally Painful. Only, the dominant arm was observed.

3.1 Dash Paired-sample t test on the overall scoring of the DASH questionnaire for pre- and post-45 min revealed a significant difference t(14) = 5.819, p < 0.00004.

3.2 Selected Functional Movement Assessment In the SFMA, both Upper Extremity Pattern 1 (MRE) and Upper Extremity Pattern 2 (LRF) observed significant differences, p < 0.0001 and p < 0.0004, respectively. There was no significant difference found for the Overhead Deep Squat (ODS) (p > 0.164).

4 Discussion This study aims to determine the effect of applying kinesiology tape (KT) on shoulder pain and mobility among (N = 15) badminton players. KT application on the shoulder was found to provide a statistically significant effect on pain scores with 45 min of use as well as shoulder medial and lateral rotational functional movements (MRE and LRF). In this study, we found that there was a decrease in shoulder pain post-45 min after the usage of KT (as shown in Table 1). Although the study found significant effects on the usage of KT, it is worth to note that previous studies have shown inconsistencies in the findings associated with the effect of KT. Studies within different populations

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and short-term KT application on the shoulder have shown no effect on shoulder stability, range of motion, and functional performance in healthy college-age adults (Perry and Lippincott 2020) and post-stroke patients (Kalichman et al. 2016). A systematic review on musculoskeletal injury population by Mostafavifar et al. (2012) also found insufficient evidence to support the use of KT following musculoskeletal injury. Although not significant, they mentioned that a perceived benefit cannot be discounted. As the usage of KT in sports becomes more popular, there is still limited and contradictory evidence on the role of KT in treating shoulder pain and psychological effects (Ghozy et al. 2020). These inconsistencies are potentially caused by a lack of consensus on how to administer the KT appropriately. A correct application of KT adhering to the taping method is considered to be associated with its efficacy (Lee 2015); therefore, appropriate technique and knowledge of the practitioner to ensure correct application are warranted. The certified physiotherapist involved in this study was to address this issue. Observing the duration of the tape applied is also of importance as KT is usually worn for several days before taking off; therefore, the immediate effect of KT application is still questionable. As shown in this study, our participants showed significant improvement in pain within 45 min of KT application and this was aligned to findings by previous studies where they have observed improvements of their athlete’s performance in the first 0 to 45 min (Han et al. 2015; Hanson et al. 2019). As well as in this study, 45 min of use improved the Upper Extremity Pattern 1 (MRE) and Upper Extremity Pattern 2 (LRF) which assess the medial rotation extension and lateral rotation flexion of the shoulder. Moreover, it is important to note that the markers measured in the study are limited to the pain questionnaire (DASH) and SFMA observation of the shoulder range of motion. A real-world sporting performance would provide better insights into the effectiveness of KT such as the systematic review done by Reneker et al. (2018). The systematic review showed that there were no significant effects in favor of KT when compared to other tapes (sham or second intervention) during dynamic tasks. Although no significant effect has been observed in the review, they have also mentioned that KT was applied at a variety of timeframes which may cause the variation in the findings. The associated different dynamic tasks included in the review such as ball skills; power squats; cycling; dynamic balance; jumping (vertical and horizontal); agility; sprint speed; and distance running might also reflect on the different parts of taping on the body that contribute toward the various results in the literature. Moving forward, we deemed that it is important to initiate consensus on how to administer KT at different body parts and timeframe of measurement to ensure consistency throughout the literature. A define level of agreement associated with KT administration will help to produce more comparable, distinguished, and directive literature. To date, evidence-base associating with the effects of KT are limited and contradictory. To avoid further discrepancies, a change in approach to create stronger evidence may well be necessary.

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5 Limitation This study was only limited to the pain questionnaire (DASH) and SFMA observations in a controlled setting. Therefore, the findings of the study should not be used to translate real-world or in-game sporting performance associated with the usage of KT.

6 Conclusion The study found that there were significant differences for pre- and post-DASH scoring (p < 0.05), as well as both Upper Extremity Pattern 1 (p < 0.0001) and Upper Extremity Pattern 2 (p < 0.0004) from the SFMA, though not for the Overhead Deep Squat (p > 0.164). Overall, KT has a beneficial effect on minimizing shoulder pain and improving shoulder mobility in badminton players. The study also deemed that it is important to initiate consensus on how to administer KT at different body parts and timeframe of measurement to produce more comparable, distinguished, and directive literature. To date, evidence-base associating with the effects of KT are limited and contradictory; therefore, a change in approach to create stronger evidence may well be necessary.

References Ansari M, Mahdavi SB, Vahdatpour B, Lahijanian A, Khosrawi S (2022) Effects of dry needling and low-power laser for the treatment of trigger points in the upper trapezius muscle: a randomized clinical trial. J Chiropractic Med Arora M, Shetty SH, Khedekar RG, Kale S (2015) Over half of badminton players suffer from shoulder pain: is impingement to blame? J Arthroscopy Joint Surg 2:33–36 Beaton DE, Katz JN, Fossel AH, Wright JG, Tarasuk V, Bombardiar C (2001) Measuring the whole or the parts? Validity, reliability, and responsiveness of the disabilities of the arm, shoulder and hand outcome measure in different regions of the upper extremity. J Hand Ther 14(2):128–146 Brox JI, Staff PH, Ljunggren AE, Brevik JI (1993) Arthroscopic surgery compared with supervised exercises in patients with rotator cuff disease (stage II impingement syndrome). BMJ 307(6909):899–903 Brox JI, Gjengedal E, Uppheim G, Bøhmer AS, Brevik JI, Ljunggren AE, Staff PH (1999) Arthroscopic surgery versus supervised exercises in patients with rotator cuff disease (stage II impingement syndrome): a prospective, randomized, controlled study in 125 patients with a 212-year follow-up. J Shoulder Elbow Surg 8(2):102–111 Butler D, Funk L, Mackenzie TA, Herrington LC (2015) Sorting swimmers shoulders: an observational study on swimmers that presented to a shoulder surgeon. Int J Shoulder Surg 9(3):90–93. https://doi.org/10.4103/0973-6042.161444 Cook G (2010) Movement: functional movement systems: screening, assessment. Corrective strategies, 1st edn. On Target Publications, Aptos, CA, pp 73–106

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Fahlström M, Söderman K (2007) Decreased shoulder function and pain common in recreational badminton players. Scand J Med Sci Sports 17(3):246–251. https://doi.org/10.1111/j.16000838.2006.00562.x Farquharson C, Greig M (2015) Temporal efficacy of kinesiology tape versus traditional stretching methods on hamstring extensibility. Int J Sports Phys Ther 10(1):45 Gabel CP, Michener LA, Burkett B, Neller A (2006) The upper limb functional index: development and determination of reliability, validity, and responsiveness. J Hand Ther 19(3):328–348 Ghozy S, Dung NM, Morra ME, Morsy S, Elsayed GG, Tran L, Huy NT (2020) Efficacy of kinesio taping in treatment of shoulder pain and disability: A systematic review and meta-analysis of randomised controlled trials. Physiotherapy 107:176–188 Glaws KR, Juneau CM, Becker LC, Di Stasi SL, Hewett TE (2014) Intra- and inter-rater reliability of the selective functional movement assessment (sfma). Int J Sports Phys Ther 9(2):195–207 Han JT, Lee JH, Yoon CH (2015) The mechanical effect of kinesiology tape on rounded shoulder posture in seated male workers: a single-blinded randomized controlled pilot study. Physiotherapy Theor Pract 31(2):120-125. https://doi.org/10.3109/09593985.2014.960054 Hanson JH, Ostrem JD, Davies BL (2019) Effect of kinesiology taping on upper torso mobility and shoulder pain and disability in US masters national championship swimmers: an exploratory study. J Manipulative Physiol Ther 42(4):247–253 Harrington S, Meisel C, Tate A (2014) A cross sectional study examining shoulder pain and disability in division I female swimmers. J Sport Rehabil 23(1):65–75 Hensley LD, Paup DC (1979) A survey of badminton injuries. Br J Sports Med 13(4):156–160 Hibberd EE, Myers JB (2013) Practice habits and attitudes and behaviors concerning shoulder pain in high school competitive club swimmers. Clin J Sport Med 23(6):450–455 Jørgensen U, Winge S (1987) Epidemiology of badminton injuries. Int J Sports Med 8(06):379–382 Kalichman L, Frenkel-Toledo S, Vered E, Sender I, Galinka T, Alperovitch-Najenson D, et al (2016) Effect of kinesio tape application on hemiplegic shoulder pain and motor ability: a pilot study. Int J Rehabil Res 39(3):272–276 Kalron A, Bar-Sela S (2013) A systematic review of the effectiveness of Kinesio taping—fact or fashion. Eur J Phys Rehabil Med 49(5):699–709 Kase K, Wallis J, Kase T (2003) Clinical therapeutic applications of the kinesio taping method. Ken Ikai Co Ltd, Tokyo, Japan Lee JH (2015) The kinesio taping technique may affect therapeutic results. J Physiother 61(4):231 Lee K, Yi CW, Lee S (2016) The effects of kinesiology taping therapy on degenerative knee arthritis patients pain, function, and joint range of motion. J Phys Ther Sci 28(1):63–66 McClure P, Greenberg E, Kareha S (2012) Evaluation and management of scapular dysfunction. Sports Med Arthrosc Rev 20(1):39–48 Montalvo AM, Cara EL, Myer GD (2014) Effect of kinesiology taping on pain in individuals with musculoskeletal injuries: systematic review and meta-analysis. Physician Sports Med 42(2):48– 57. https://doi.org/10.3810/psm.2014.05.2057 Mostafavifar M, Wertz J, Borchers J (2012) A systematic review of the effectiveness of kinesio taping for musculoskeletal injury. Phys Sportsmed 40(4):33–40. https://doi.org/10.3810/psm. 2012.11.1986 Perry CM, Lippincott EL (2020) The effects of kinesiology tape on shoulder stability and functional performance Phomsoupha M, Laffaye G (2020) Injuries in badminton: a review. Sci Sports 35(4):189–199 Reneker JC, Latham L, McGlawn R, Reneker MR (2018) Effectiveness of kinesiology tape on sports performance abilities in athletes: a systematic review. Phys Ther Sport 31:83–98 Roe Y, Soberg HL, Bautz-Holter E, Ostensjo S (2013) A systematic review of measures of shoulder pain and functioning using the international classification of functioning, disability and health (ICF). BMC Musculoskelet Disord 14(1):73 Roy J, MacDermid J, Woodhouse LJ (2009) Measuring shoulder function: a systematic review of four questionnaires. Arthritis Care Res 61(5):623–632

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Ticker JB, Fealy S, Fu FH (1995) Instability and impingement in the athlete’s shoulder. Sports medicine Woodward KA, Unnithan V, Hopkins ND (2015) Forearm skin blood flow after kinesiology taping in healthy soccer players: an exploratory investigation. J Athl Train 50(10):1069–1075 Yung PS, Chan RH, Wong FC, Cheuk PW, Fong DT (2007) Epidemiology of injuries in Hong Kong elite badminton athletes. Res Sports Med (print) 15(2):133–146. https://doi.org/10.1080/ 15438620701405263

Effects of Wheel Depth on Individual Time Trial Performance Among Skilled Cyclists Mohd Azka Nabil, Hosni Hasan, Mohd Shariman Ismadi Ismail, and Mohd Azim Nural Azhan

Abstract Wheels rotation can produce aerodynamic drag during cycling, and cyclists need to overcome this resistance to complete the race as fast as they can. This study aimed to investigate the effects of wheel depths (low and high) in a selected variable toward individual time trials among skilled cyclists. Thirteen participants were recruited for the 6 km cycling testing sessions, and they underwent two types of cycling conditions: the low wheel depth (low, 20 mm) and high wheel depth (high, 50 mm) wheelset in a cross-over design. Time trial (in minutes), average speed (km/h), top speed (km/h), sprint time (in seconds), and rate of perceived exertion were measured in both wheel depth cycling conditions. The results show significant differences (p < 0.05) in terms of the time trial, average speed, and top speed where the high wheel depth is proven to be better in maintaining speed and achieving top speed. Meanwhile, there is no significant difference (p > 0.05) in terms of sprint time taken for both wheels. The tailwind gave the high wheel depth a boost for its larger surface area than the low wheel depth wheelset indicating high wheel depth is better at reducing the aerodynamic drag. Thus, this study favored the high wheel depth wheelset (50 mm) which will give a better result in terms of speed compared to the low wheel depth wheelset (20 mm). Keywords Cycling · Wheel depth · Skilled cyclists

M. A. Nabil · H. Hasan (B) · M. S. I. Ismail Faculty of Sports Science and Recreation, Universiti Teknologi MARA, 40450 Shah Alam, Malaysia e-mail: [email protected] H. Hasan · M. A. N. Azhan Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Cawangan Perlis, Kampus Arau, 02600 Arau, Perlis, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_5

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1 Introduction There are many types of competitive cycling which are road cycling, off-road mountain biking, downhill, and BMX. Road cycling is the most famous out of them all in terms of numbers of athletes who participated, events, and audience. A lot of variables were tested, and key points were mentioned in many studies from physiology and biomechanics perspectives to enhance cycling performance. Aerodynamic drag plays a vital role in determining cycling performance (Barry et al. 2015). Cycling at a higher speed will result in a greater aerodynamic drag for the cyclist to overcome (Miau et al. 2020). Back in Tour de France 2007, in an individual time trial event, a 40-s gap was made between the 3rd and 8th riders that are approximately equivalent to 1% of aerodynamic drag (Godo et al. 2009) in a race that is slightly more than one hour. Hence, every second in a cycling race is important, especially in a much longer race. Most bicycle companies such as Zipp, Specialized, Mavic, Fulcrum, and Shimano tested their rim in the wind tunnel before manufacturing it in a large scale. It ensures high performance and an increase in performance from a biomechanics perspective for the cyclist. Most wheels are deemed as factory built, and most of the wheels made were built by hand. Regarding the previous statement, each wheel has its own characteristics that vary even though they are made from the same initial design and material. In road cycling, aerodynamic drag can be measured up to 90% (Giljarhus et al. 2020). Based on Godo et al. (2011), a high depth wheel is better at reducing drag value when being compared with a low depth wheel. It has been found that putting a splitter plate will increase the depth in wheel structure and has been proven to reduce drag by as much as 5%. Large-scale studies have been experimented to study more about the drag force effect on a cyclist in the last 20 years. Most studies use wind tunnel technology to calculate and find the value of aerodynamic drag onto the cyclist through computational fluid dynamics. From a biomechanics perspective, Pogni et al. (2015) mentioned that wheels act as a critical variable in determining the balance of the rider because crosswinds’ presence can reduce cyclists’ stability while cycling. A study by Fintelman et al. (2014) discovered that aerodynamic side force could increase as much as 2.5 times more than the actual aerodynamic drag force. In addition, the road bike is accountable for holding up to 60% lateral force coefficient on large yaw angles during crosswinds. This condition will most likely cause cyclists to fall off their bikes if full control over the bike cannot be achieved in time. In a road race grand tour where a large peloton is indirectly close in contact, one accident will disrupt the one whole group due to the presence of crosswind. These findings have been supported by Fintelman (2015) where the experiments he conducted have resulted in aerodynamics forces being affected by the presence of crosswinds. Blocken et al. (2020) also mentioned that a motorcycle could give a cyclist a significant advantage by reducing aerodynamic drag even though the distance drafted is unnoticed by the naked eye. The result has shown that a 50-m gap

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between a cyclist and a motorcycle during drafting can save up to 1.6 s per kilometer. Hence, it is crucial to determine the type of wheel used in a specific terrain. Almost all previous studies used a wind tunnel to understand the wind flow structure but never considered adding other forces such as side forces and different kinds of terrain structures. Out of all studies, only one experiment mimics the real-world condition where a method called the Ring of Fire was conducted (Spoelstra et al. 2019). Only a few studies have taken action in taking the test into the real-world condition where the external forces could take action on the cyclist when performing the task (Fintelman et al. 2014).

2 Material and Methods 2.1 Participants Thirteen skilled male cyclists from the local cycling team were recruited as participants in this study. Participants were experienced and competitive cyclists with more than 4 years of experience (Hasan et al. 2016). The participants’ mean age was 21.23 ± 2.088 years, height (169.62 ± 3.863 cm), and weight (65.52 ± 8.788 kg). All testing procedures in this study involving human participants were approved by University Teknologi MARA ethical committee (REC/09/2021) (MR/789).

2.2 Methodology All participants used the standardized road racing bicycles (Polygon Helios 400) during cycling in both conditions (low and high wheel depth). The road bike has an aluminum-type frame model ALX SL 6XXX with Columbus full carbon fork. The drop bar, seat post, and stem are using Ritchey brand components. The front shifters, crankset, and derailleur were from Shimano 105 2 × 10 group set. The cassette for the bicycle is Shimano Tiagra 10 speed with SRAM chain ring, while the saddle is Fizik Alliante Gamma. The paddle was varied between each cyclist due to the compatibility of their shoes for comfort. The bike’s weight were varied depending on the different wheelset equipped: the Shimano Ultegra (Conventional, low depth wheel) and Shimano RS80 C50 (High depth wheel). Information regarding the wheel depth characteristic used in this study is provided in Table 1. In addition, the bicycle also was equipped with Garmin Edge power meter that provides information on the current speed, average speed, maximum speed, trip distance, total distance, elapsed time, and clock. For extra-precise climb and descent data, the device incorporates a barometric altimeter to pinpoint elevation changes. The new activity profiles feature allows cyclists to customize data fields and device settings based on their cycling activity, such as training, racing, or road and mountain

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Table 1 Low and high wheel depth characteristics Type

Low depth wheel

High depth wheel

Name

WH-RS500 or the Shimano Ultegra wheelset

Shimano RS80 C50 or WH-RS80 Ultegra wheelset

Wheel Depth

24mm/20.8mm

50mm

Material

Aluminum

Carbon

Spoke count

16 front/20 rear

16 front/20 rear

Weight

1649 g

1875 g

Tire

Tubeless

Clincher

biking. It has been used in past studies as in Hurst et al. (2017) and in the GarminSharp Pro Team. This study utilized experimental research using a cross-over design. All participants were randomly assigned into two groups prior to the testing sessions. The first group of seven cyclists rode the low depth wheelset first, while the second group of six cyclists rode the high depth wheelset. The cycling conditions were swapped after the first cycling trials. All participants were asked to ride with maximum effort in a 6.0 km, U-shaped curved road on an individual time trial. A period of 60 min was given to the participants as a wash-out period to prevent any effect of performance disruption before proceeding to the next testing session. The time taken and top speed were recorded once they had reached the finish line. A 100-m sprint time taken was taken at points A and B by an observer using a stopwatch on both points during the testing alongside the time taken and top speed. A stopwatch was used because it is to accurately calculate the distance of the 100-m sprint in both points and it is impossible to take the time taken using the power meter specifically in that particular phase. Lastly, a cooling down session was conducted led by their head coach to avoid and reduce any possibility of injury that could happen to the participant. A Statistical Package for Social (SPSS) version 26.0 was used to analyze the data. All the data variables are applied using descriptive statistics through the presentation of mean and standard deviation. Paired sample t tests were used to analyze the effects of wheel depth conditions in individual time trial cycling, and the significant value was set at p < 0.05.

3 Results Table 2 below described the descriptive statistics for time trial, average speed, top speed, and sprint time taken for both conditions which are low wheel depth and high wheel depth by the participants. The fastest time for low wheel depth wheel is 8.10 min and 12.03 min as the slowest time trial with 9.301 ± 1.151 min as mean and standard deviation. As for the high wheel depth, the fastest time trial is 8.07 min and 11.56 min as the slowest time trial with 9.117 ± 1.073 min as the mean and standard

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Table 2 Collected cycling variables for low and high wheel depth conditions Wheel depth conditions

Time trial (mins)

Average speed (km/h)

Top speed (km/h)

Sprint time taken A (s)

Sprint time taken B (s)

Low

9.30(1.15)

39.22(4.45)

47.38(3.23)

3.61(0.3)

3.60(0.42)

High

9.12(1.07)

39.96(4.32)

48.22(3.75)

3.60(0.32)

3.51(0.30)

P values

0.005

0.006

0.045

0.801

0.412

deviation. Meanwhile, the lowest average speed for low wheel depth is 29.93 km/h and the fastest is 44.44 km/h with the mean and standard deviation of 39.218 ± 4.453 km/h. The high wheel depth has the lowest average speed of 31.14 km/h, and the highest average speed is 44.61 km/h with a standard deviation of 39.952 ± 4.319 km/h. As for the top speed for low wheel depth, the participants’ minimum top speed is 42.30 km/h and maximum top speed of 53.70 km/h with the mean and standard deviation of 48.215 ± 3.237 km/h. The high wheel depth has the minimum top speed of 42.00 km/h and maximum of 52.30 km/h with the mean and standard deviation of 47.377 ± 3.752. The sprint time taken for A-20 has the lowest time taken of 3.21 s and highest as 4.11 s with a standard deviation of 3.613 ± 0.312 s. The sprint taken for A-50 have the same value as A-20 as the minimum value which is 3.21 s and the highest as 4.13 s with the mean and standard deviation of 3.599 ± 0.324 s. Lastly, the sprint time taken for B-20 is the lowest time taken of 3.17 s and the highest as 4.51 s with the mean and standard deviation of 3.584 ± 0.416 s. The lowest sprint time taken for B-50 is 3.13 s and 4.17 as the highest with the mean and standard deviation of 3.507 ± 0.302 s. An observation was made, and it was found that high wheel depth prevails in almost all the variables as it was recorded as the fastest time in the time trial, highest in average speed, and fastest in sprint time taken in both points A and B. The high wheel depth shows a better quality in terms of time taken, average speed, and sprint time taken in both point A and B when being compared with low wheel depth wheelset. However, the low wheel depth wheel only prevails at the overall top speed where it increases around 1.74% in terms of mean. The maximum speed between both conditions shows a 2.61% in difference of the highest value of top speed which is equivalent to 1.4 km/h. Meanwhile, the fastest time taken for point A for both wheel conditions has the same value but in terms of mean, high wheel depth shows a better and faster speed. Paired t test analysis showed that there was a significant difference between low and high wheel depth on time trial (t = 3.483, df = 12, p < 0.05), average speed (t = −3.287, df = 12, p < 0.05), and top speed (t = 2.241, df = 12, p < 0.05) among the cyclists.

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4 Discussions The main objective of this experimentation was to investigate the effect of two different wheel depths which is low wheel depth and high wheel depth in terms of time trial, average speed, top speed, and sprint time taken at different points among skilled cyclists. This study found that high wheel depth showed a better quality in terms of time trial, average speed, and top speed. This finding was supported by Godo et al. (2011), and stating high depth wheel is better at reducing aerodynamic drag value when being compared with a low depth wheel, thus producing more energy efficient to the cyclists (Arora et al. 2019). An increment of a splinter in the depth of wheel structure increases significantly in quality showing it can reduce the aerodynamic force as much as 5%. With that being said, an observation was made, and the participant stated that there was side wind present during the testing day. Barry et al. (2012) discovered that as high as 38% of side forces reacted on a cyclist using a full covered wheel—disk wheel as in being compared to a spoke wheel. However, during the change of direction during turning to the finishing line, the sidewind seems to be likely to help the participants to propel forward as in tailwind during the turnover. Although there was a presence of side wind, the high wheel depth wheel still prevails maybe mainly because of the change of direction during the U-Turn after point A that helps the cyclist to increase their momentum to the finishing line. Besides, the track also is mostly of flat roads that could benefit the high wheel depth in keeping up its momentum. In addition, with the help of the tail wind, it was much easier for the high wheel depth wheel to accelerate where it shows the average time taken for sprint time taken in points A and B for high wheel depth wheel was faster than sprint time taken for low wheel depth wheel where it showed there is benefit in the presence of side-tail wind during the turnover. Next, it also has been observed that different cyclists have different positioning, especially when performing an individual time trial. All the participants are free to choose what kind of position they are willing to use during the testing. Different positioning and shape of the handlebars play important influence in determining the drag area of the incoming aerodynamic drag. García-López et al. (2008) mentioned that the aerodynamic drag decreases as much as 14% when the handlebars moved forward, making the body posture or positioning of the cyclist more aerodynamic hence less contact to the incoming drag force. Most of them mimic the individual time trial position even though the bicycle is only equipped with a drop bar instead of a time trial bar. The performance of this testing would vary in terms of the variables stated accordingly if it was taken in a different population, level of exposure, latitude, and longitude. In addition, if this study was conducted on a different kind of track and type of terrain as in using a hilly topography, it would benefit the low-profile wheelset. From a mechanical perspective, the type of equipment the cyclist wears and the weariness of the equipment after each use could affect the cyclist. As being stated by Maier et al. (2019), the equipment will influence the riding style through the small portion

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of weight that contribute to the heaviness of the bicycle and the positioning of the equipment that could influence the center of gravity of the bicycle.

5 Conclusions This study concluded that the higher the depth of the wheelset and the bigger the surface area of a wheel will contribute to better speed maintenance and faster top speed compared to the low depth wheelset. In addition, the larger surface area of the wheel will add to the weight of the entire structure needing a larger amount of energy to move up, especially on a rolling terrain or during a steep corner. However, the sidewind changed to tailwind during the turnover making it easier for the high wheel depth wheel to prevail.

References Arora BB, Bhattacharjee S, Kashyap V, Khan MN, Tlili I (2019) Aerodynamic effect of bicycle wheel cladding—a CFD study. Energy Rep 5:1626–1637 Barry N, Burton D, Crouch T, Sheridan J, Luescher R (2012) Effect of crosswinds and wheel selection on the aerodynamic behavior of a cyclist. Procedia Eng 34:20–25 Barry N, Burton D, Sheridan J, Thompson M, Brown NA (2015) Aerodynamic drag interactions between cyclists in a team pursuit. Sports Eng 18(2):93–103 Blocken B, Malizia F, van Druenen T, Gillmeier S (2020) Aerodynamic benefits for a cyclist by drafting behind a motorcycle. Sports Eng 23(1):1–11 Fintelman D, Sterling M, Hemida H, Li F-X (2014) The effect of crosswinds on cyclists: an experimental study. Procedia Eng 72:720–725 Fintelman DM (2015) Influence of cycling position and crosswinds on performance and aerodynamics. (Doctoral Dissertation) University of Birmingham García-López J, Rodríguez-Marroyo JA, Juneau C-E, Peleteiro J, Martínez AC, Villa JG (2008) Reference values and improvement of aerodynamic drag in professional cyclists. J Sports Sci 26(3):277–286 Giljarhus KET, Stave DÅ, Oggiano L (2020) Investigation of influence of adjustments in cyclist arm position on aerodynamic drag using computational fluid dynamics. Multi Digit Publishing Inst Proc 49(1):159 Godo M, Corson D, Legensky S (2009) An aerodynamic study of bicycle wheel performance using CFD. In: Proceedings of the 47th AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition, Orlando, FL, USA, 5–8 January 2009 Godo M, Corson D, Legensky S (2011) A practical analysis of unsteady flow around a bicycle wheel, fork, and partial frame using CFD. In: Proceedings of the 49th AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition, Orlando, FL, USA, 4–7 January 2011, p 1237. https://doi.org/10.2514/6.2011-1237 Hasan H, Davids K, Chow JY, Kerr G (2016) Compression and texture in socks enhance football kicking performance. Hum Mov Sci 48:102–111 Hurst HT, Sinclair J, Atkins S, Rylands L, Metcalfe J (2017) The effect of mountain bike wheel size on cross-country performance. J Sports Sci 35(14):1349–1354 Maier T, Müller B, Allemann R, Steiner T, Wehrlin JP (2019) Influence of wheel rim width on rolling resistance and off-road speed in cross-country mountain biking. J Sports Sci 37(7):833–838

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Miau J-J, Li S-R, Tsai Z-X, Phung MV, Lin S-Y (2020) On the aerodynamic flow around a cyclist model at the hoods position. J Visualization 23(1):35–47 Pogni M, Petrone N, Antonello M, Gobbato P (2015) Comparison of the aerodynamic performance of four racing bicycle wheels by means of CFD calculations. Procedia Eng 112:418–423 Spoelstra A, de Martino Norante L, Terra W, Sciacchitano A, Scarano F (2019) On-site cycling drag analysis with the ring of fire. Exp Fluids 60(6):1–16

The Psychometric Properties of the Malay Version of the Depression, Anxiety and Stress Scale (DASS-21-M) Among Smokers Nur-Hasanah Ruslan, Nur Amirah Fikriyah Muhd Suhaidi, and Siti Munira Yasin Abstract The Depression, Anxiety and Stress Scale 21 (DASS-21) is commonly used in clinical setting to screen depression, anxiety, and stress. However, the factor structure of the Malay version DASS-21 (DASS-21-M) in smokers has not yet been explored. This study aims to assess the psychometric properties of DASS-21 Malay among the smoker’s population and determine the concurrent validity of DASS21 with depression and anxiety inventory. This is a cross-sectional study with a convenience sampling method among 120 smokers. The study instruments include the Depression, Anxiety and Stress Scale (DASS-21-M), Beck Depression Inventory (BDI-M), and the Beck Anxiety Inventory (BAI-M). The data was analyzed for descriptive statistics, exploratory factor analysis, and correlation coefficient. The DASS-21-M revealed a very good total Cronbach’s alpha values of 0.80, 0.84, and 0.85, respectively, for the depression, anxiety, and stress subscales. For construct validity, the exploratory factor analysis results revealed the KMO = 0.88, and the communalities ranged from 0.49 to 0.80. The scree plot and Kaiser criteria show the three constructs with a cumulative 60.84% of initial eigenvalue. The construct validity achieved an acceptable factor loading for each construct which ranged from 0.32 to 0.78. This study showed a significant correlation between Depression, and Anxiety with BDI-M and BAI-M. However, the suitability of DASS-21 uses among smokers may require future evaluation. The results of this study entrenched the pilot evidence of the suitability of DASS-21 among smokers. N.-H. Ruslan (B) Faculty of Sport Science and Recreation, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia e-mail: [email protected] N. A. F. Muhd Suhaidi Faculty of Sport Science and Recreation, Universiti Teknologi MARA, Jengka Campus, Pahang, Malaysia S. M. Yasin Faculty of Medicine, Universiti Teknologi MARA, Sg. Buloh Campus, Sungai Buloh, Selangor, Malaysia e-mail: [email protected] Hospital Al-Sultan Abdullah, UiTM Puncak Alam, Puncak Alam, Selangor, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_6

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Keywords Psychometric · DASS-21 · Smokers

1 Introduction 1.1 Depression Anxiety Stress Scales (DASS-21) The Depression, Anxiety Stress Scales (DASS) is widely used in research, diagnosis, and clinical settings. It was initially developed by Lovibond and Lovibond in (1995), to measure the negative effects of stress, anxiety, and depression in adults using a self-reported measure. The depression factor characterizes low levels of positive effects. At the same time, anxiety is represented by physiological hyperarousal, and stress represents the characteristics like irritability, nervous tension, difficulty in relaxing, and agitation (Lovibond and Lovibond 1995). The DASS uses a 4point severity or frequency scale ranging from never to almost always to rate the participants experience each state over the past week. In adult clinical samples, high scores on the DASS Tension or Stress scale are associated with a DSM-IV (American Psychological Association 2013) and diagnosis of Generalized Anxiety Disorder, while high scores on the DASS-Anxiety scale are associated with Panic. DASS also was tested in different cultural settings and was found to be consistent across the racial spectrum (Ali et al. 2022; Norton 2007).

1.2 Smoking and Mental Health Smoking is an addictive habit and is related to nicotine dependence. People smoke for many reasons; one is to achieve emotional relief. Smoking can be due to addiction, relief from the withdrawal symptom, or relief from stress. Thus, smoking rates among people with anxiety (Moylan et al. 2012) and other mental conditions are significantly higher than in the general population (Action on Smoking and Health 2019). There is a strong association between smoking and mental health conditions. The highest levels of smoking were found in psychiatric patients (Action on Smoking and Health 2019). It was estimated that around 30% of smokers in the UK have a mental health condition, and more than 40% of adults were with a severe mental illness (Action on Smoking and Health 2019). The smoker population was also considered a substance abuse population highly associated with depression (Beaufort et al. 2017) and mental health (Lien et al. 2021). Thus, the smokers’ population differs from other populations that have been studied and tested with DASS-21(Ali et al. 2022). Moreover, the study by Beaufort et al. (2017) did not advise to use the DASS-21 to screen for depression among substance abuse populations. Hence, the suitability of these valid instruments to screen for depression in the smokers’ subpopulation is needed (Beaufort et al. 2017).

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The DASS-21 contains all the items related to depression, anxiety, and stress. It is different from the Beck Depression Inventory (BDI) and the Beck Anxiety Inventory (BAI), which were used to assess depression or anxiety alone. However, the BDI and BAI failed to distinguish between depression and other affective conditions due to several items that measured nonspecific symptoms such as weight gain. Nevertheless, different populations and cultures perceived these differences in certain ways. As demonstrated by Zanon et al. (2021), there are mixed results in the factor structure of the measure. In addition, smokers also differed from other substance abuse populations in terms of being less pleasurable (Kozlowski et al. 1989). Thus, further assessment of its factor structure and measurement invariance across countries and subpopulations is needed to be explored.

2 Method This study is an observational cross-sectional design with a convenience sampling method. One hundred twenty (n = 120) daily smokers voluntarily participated in this study. Before the data collection was started, this study received its ethical approval from UiTM’s Research Ethical Committee. The eligibility of the participants was screened for inclusion and exclusion criteria. The sample size is based on the one item per five participants ratio, with an additional 20% added to allow for missing data. The participants are from residences in the Kuantan area in Pahang.

2.1 Study Instruments Several sociodemographic characteristics were collected from the participants, which include age and marital status, level of education, employment status, and smoking history information. The Malay Depression, Anxiety and Stress Scale (DASS-21-M) was used in this study. The DASS-21 consisted of 21 items with three domains. There are seven items on each scale of the DASS-21 questionnaire (DASS-Depression scale, DASS-Anxiety scale, and DASS-Stress scale, respectively). It was translated and validated into Malay with a Cronbach alpha coefficient of 0.84 (depression), 0.74 (anxiety), and 0.79 (stress). It also had a good loading factor which ranged between 0.39 and 0.73 for all the items, and the correlations among the three scales were between 0.54 and 0.68 (Musa et al. 2007). For the Malay Beck Anxiety Inventory (BAI-M), the original version was developed by Beck et al. (1988). The BAI consisted of a 21-item self-reported measure with a list of anxiety symptoms. Participants responded to questions that measured how much each symptom bothered them over one week. The higher scores indicated more severe anxiety symptoms. The symptoms were rated on a four-point scale, ranging from “not at all” (0) to severely (3). The Malay version was validated by

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Mukhtar and Zulkefly (2011), with Cronbach alpha coefficients ranging from 0.66 to 0.89 and a satisfactory overall alpha value of 0.91. The original BDI was developed to assess the severity of depression among psychiatric patients and depression in a general population. This inventory consisted of 21 items which measured cognitive, affective, somatic symptoms, and neuro vegetative and endogenous aspects of depression. It was rated on a four-point scale ranging from 0 (no symptom) to 3 (severe symptom). The BDI score was obtained by totaling the ratings for each of the 21 items. The overall depression scores ranged from 0 to 63. Scores of 0 to 9 were considered the normal range or asymptomatic; scores of 10 to 15 indicated mild depression, 16 to 23 indicated moderate depression and 24 to 63 indicated highly severe depression. The Malay Beck Depression Inventory (BDI-M) was used in this study, with an internal consistency ranging from 0.56 to 0.87 (Quek et al. 2001). The data for the study were analyzed using the IBM SPSS Statistics software, version 27.0 to provide the descriptive statistics for mean and standard deviation, exploratory factor analysis using Principal Axis Factoring (PAF) extraction, and Varimax as the rotation method. Reliability analysis was done using interclass correlation (Two-Way method) or ICC. In contrast, the average measure and Pearson correlation coefficient for normally distributed data based on Skewness and Kurtosis were less than 1.96 (Kim 2013).

3 Results As shown in Table 1, this study shows that the participant’s mean age was 26.9 ± 11.8 years, with the age of starting to smoke about 13.61 ± 1.4 years. And the average number of cigarettes smoked per day was 10.88 ± 4.6 sticks. The participants were mostly single, 72.5% (n = 87), followed by married subjects, 25% (n = 25), and widowers 2.5% (n = 3). The participants’ job categories also were mostly among students at 51.6% (n = 62), private staff of private companies with 26.7% (n = 32), government staff at 9.2% (n = 11), self-employment at 7.5% (n = 9), and unemployed at 6% (n = 5). For exploratory analysis, the KMO value was 0.88. The p < 0.001 indicated that the data was adequate, while communalities ranged from 0.49 to 0.81 (see Table 2). The Kaiser criteria cumulative % (eigenvalue > 1) was about 60.84% with three factors extracted and supported (see Fig. 1). The internal consistency of the total DASS-21 was 0.94, whereas the DASS-21 subscales for depression, anxiety, and stress were 0.80 (CI = 0.73 to 0.84), 0.84 (CI = 0.54 to 0.83), and 0.85 (CI = 0.80 to 0.88), respectively. The mean (SD), skewness and kurtosis for DASS-21 subscales for this study as shown in table (see Table 3). The items and their factor loading were shown in Table 4. There were 14 items that were loaded in anxiety, six items had no cross-loading, seven items had crossloading of more than 0.32 and only one item was loaded as cross-loading. For stress, there were 13 items loaded, five items without cross-loading, seven items loaded as

The Psychometric Properties of the Malay Version of the Depression, … Table 1 The participant’s sociodemographic (n = 120)

Sociodemographic

Mean (SD)

Age

26.9 (11.8)

Age of start smoke

13.66 (1.4)

No. of cigarettes per day

10.88 (4.6)

53 n (%)

Marital status Single

87 (72.5)

Married

30 (25)

Widower

3 (2.5)

Job categories

Table 2 DASS-21 items characteristics

Self-employments

9 (7.5)

Students

62 (51.6)

Private staff

32 (26.7)

Governments staff

11 (9.2)

Unemployed

6 (5)

Items

Mean (SD)

Communalities

Factor loading

Dass_1

1.41 (0.64)

0.629

0.679

Dass_2

0.81 (0.69)

0.541

0.624

Dass_3

1.21 (0.96)

0.517

0.624

Dass_4

0.46 (0.59)

0.717

0.797

Dass_5

1.08 (0.48)

0.581

0.516

Dass_6

1.13 (0.55)

0.571

0.584

Dass_7

1.23 (0.56)

0.633

0.528

Dass_8

1.33 (0.52)

0.569

0.631

Dass_9

1.56 (0.68)

0.607

0.746

Dass_10

1.58 (0.63)

0.768

0.634

Dass_11

1.54 (0.65)

0.694

0.585

Dass_12

0.83 (0.59)

0.632

0.594

Dass_13

0.86 (0.57)

0.596

0.573

Dass_14

1.33 (0.68)

0.643

0.562

Dass_15

0.62 (0.65)

0.674

0.580

Dass_16

1.50 (0.64)

0.625

0.627

Dass_17

1.63 (0.60)

0.592

0.600

Dass_18

1.08 (0.50)

0.488

0.484

Dass_19

1.14 (0.69)

0.749

0.719

Dass_20

1.91 (0.71)

0.804

0.779

Dass_21

1.87 (0.70)

0.801

0.781

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Fig. 1 Scree plot for DASS-21 items

Table 3 Mean (SD), skewness, and kurtosis for depression, anxiety and stress subscales for this study Depression Skewness Kurtosis Anxiety Skewness Kurtosis Stress Skewness Kurtosis M (SD) (SE) (SE) M (SD) (SE) (SE) M (SE) (SE) (SD) 9.71 (3.13)

0.77 (0.22)

0.51 (0.44)

15.43 (6.58)

1.35 (0.22)

1.65 (0.44)

17.30 1.13 (6.0) (0.22)

1.10 (0.44)

M mean, SD standard deviation, SE Standard error

cross-loading, and one item with cross-loading of more than 0.32. For the depression subscale, only two items loaded and all the items have cross-loading but not more than 0.32. All DASS-21 subscales show a positive and strong correlation with BDI and BAI scores in Table 5. Thus, it indicates that the concurrent validity had been achieved.

4 Discussion This study revealed that the Malay DASS-21 had good psychometric values for internal consistencies and exploratory factor analysis. KMO value was more than 0.88, indicating the sample adequacy for factor analysis. Keiser criteria also showed the items at 60.84%, which was more than 50 percent, representing the scales for this tested subpopulation. This study yielded Cronbach’s alpha values of 0.80, 0.84, and 0.85 compared to 0.80, 0.74, and 0.79, respectively, for depression and anxiety in a previous study

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Table 4 The DASS-21 and its items factor loading Item

Original subscales

Loading Anxiety

Stress

Depression

Dass_1

Stress

0.679

Dass_2

Anxiety

0.624

Dass_3

Depression

0.797

Dass_4

Anxiety

0.516

0.384*

Dass_5

Depression

0.584

0.404*

Dass_6

Stress

0.528

0.494*

Dass_9

Anxiety

0.430

0.634*

Dass_10

Depression

0.594

0.378*

Dass_12

Stress

0.594

Dass_13

Depression

0.573

Dass_15

Anxiety

0.580

Dass_18

Stress

0.484

Dass_19

Anxiety

0.719

Dass_7

Anxiety

0.631

Dass_8

Stress

0.746

Dass_11

Stress

Dass_14

Stress

Dass_16

Depression

0.627

Dass_17

Depression

0.600

Dass_20

Anxiety

0.779

Dass_21

Depression

0.781

*

0.361*

0.357*

0.585 0.562*

0.511

cross-loading, bold italic = original subscales, bold item = item from other subscale

Table 5 DASS-21 subscales correlation with BDI and BAI scores

BDI

BAI

DASS_depression

r = 0.601*

r = 0.683*

DASS_anxiety

r = 0.619*

r = 0.710*

DASS_stress

r = 0.544*

r = 0.592*

r = correlation efficient, * P < 0.001

among diabetic patients (Ramli et al. 2009). This study has shown that most items are loaded with anxiety followed by stress and depression. For exploratory factor analysis, items considered have cross-loading when the item has another factor loading, with values of more than 0.32 (Costello and Osborne 2005). In this present study, there were eight items had cross-loading, thus providing poor outcomes for the current study. In this sample, only six anxiety items, four stress items, and two items

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were loaded on depression without cross-loading loaded in the respective subscales compared to the supposed seven items, respectively. This study revealed that high cross-loading indicated a very high level of multicollinearity for this tested sample. Most of the items were loaded in anxiety (n = 14), five from stress, and another four from depression. This phenomenon might be due to the high positive correlation between anxiety and stress found in the previous study on diabetic patients (Ramli et al. 2009). Interestingly, it also happened in this sample group because the DASS-21 might not be able to discriminate between the overlapping symptoms of depression and strong emotions associated with substance abuse (Beaufort et al. 2017). In addition, the dependence level toward the other substance abuse also needs to be considered. The other critical aspect observed in the exploratory factor analysis is that there was too much cross-loading among the subscales. This might be due to the nature of the subpopulation. This study indicated that the smokers perceived anxiety and stress as similar. This study also found that the sample group showed the mean of BDI was around 21, which is moderate depression and BAI anxiety means score is 26, which is a moderate anxiety level. Similarly, the DASS score showed moderate depression and extreme severe for anxiety and stress levels. These characteristics were consistent with previous studies, which illustrated that depressive symptoms experienced by diabetes patients were significantly related to anxiety and stress, as suggested by Zhang et al. (2008) in their study among Type 2 Diabetes patients. The items and cross-loading might influence the respondents’ characteristics. Thus, this study assumed that the way respondents perceived the experiences mainly caused the differences in the findings. However, a future study on the smoker population must confirm these assumptions. Nevertheless, since this is the first study testing the DASS-21 among smokers in the Malaysian population, it was found to be different from other clinical samples such as diabetes patients. However, this study does show that the DASS-21 subscales had significantly high correlations between depression and anxiety. It should be noted that this study also had a limitation in that the study population was only Malay male representatives and was only limited to one locality in Malaysia, while it may not represent the Malaysian population. There was also no measure for nicotine dependence, making the possibility that non-addicted respondents or non-daily smokers were included. From this recent study, we can conclude that most of the items in DASS-M were loaded in different subscales and also had high multicollinearity. This study can be a pilot finding as a baseline for future studies. Therefore, the use of the DASS21 among the smoker population needs to be further evaluated. Further efforts on criterion validity of the DASS-21 should be further conducted with other related criteria such as nicotine-dependent tests like the Fagerström test and mental health questionnaires. Future studies should also have more numbers as their sample size in order to have one item and 10 respondents ratio and run the confirmatory factor analysis for further details.

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References Action On Smoking and Health (2019) Fact sheet No. 12: smoking and mental health 12:1–11 Ali AM, Hori H, Kim Y, Kunugi H (2022) The depression anxiety stress scale 8-items expresses robust psychometric properties as an ideal shorter version of the depression anxiety stress scale 21 among healthy respondents from three continents. Front Psychol 13(March). https://doi.org/ 10.3389/fpsyg.2022.799769 American Psychological Association (2013) Diagnostic and statistical manual of mental disorders, 5th edn (DSM-5) Beaufort IN, Oene HDW, Buwalda AJ (2017) The depression, anxiety and stress scale (DASS-21) as a screener for depression in substance use disorder inpatients: a pilot study. 260–268. https:// doi.org/10.1159/000485182 Beck, Brown, Epstein, Steer (1988) An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol 56(6):893–897 Costello AB, Osborne JW (2005) Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. Pract Assess, Res Eval 10(7). https://doi.org/10. 7275/jyj1-4868 Kim H-Y (2013) Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis. Restorative Dentist Endod 38(1):52. https://doi.org/10.5395/rde.2013. 38.1.52 Kozlowski LT, Wilkinson DA, Skinner W, Kent C, Franklin T, Pope M (1989) Comparing tobacco cigarette dependence with other drug dependencies: greater or equal difficulty quitting and urges to use, but less pleasure from cigarettes. JAMA 261(6):898–901. https://doi.org/10.1001/jama. 1989.03420060114043 Lien L, Bolstad I, Bramness JG (2021) Smoking among inpatients in treatment for substance use disorders: prevalence and effect on mental health and quality of life. BMC Psychiatry 21(1):1–9. https://doi.org/10.1186/s12888-021-03252-9 Lovibond PF, Lovibond SH (1995) The structure of negative emotional states: comparison of the depression anxiety stress scales (DASS) with the beck depression and anxiety inventories. Pergamon 33(3):335–343 Moylan S, Jacka FN, Pasco JA, Berk M (2012) Cigarette smoking, nicotine dependence and anxiety disorders: a systematic review of population-based, epidemiological studies. BMC Med 10(1):123. https://doi.org/10.1186/1741-7015-10-123 Mukhtar F, Zulkefly N (2011) The beck anxiety inventory for Malays (BAI-Malay): a preliminary study on psychometric properties. Malays J Med Health Sci 7(1):73–79 Musa R, Fadzil MA, Zain Z (2007) Translation, validation and psychometric properties of Bahasa Malaysia version of the depression anxiety and stress scales (DASS). ASEAN J Psychiatry 8:82–89 Norton PJ (2007) Depression anxiety and stress scales (DASS-21): psychometric analysis across four racial groups. Anxiety Stress Coping 20(3):253–265. https://doi.org/10.1080/106158007 01309279 Quek KF, Low WY, Razack AH, Loh CS (2001) Beck depression inventory (BDI): a reliability and validity test in the Malaysian urological population. Med J Malaysia 56(3):285–292 Ramli M, Salmiah M, Nurul Ain M (2009) Validation and pychometric properties of Bahasa Malaysia version of the depression anxiety and stress scales (DASS) among diabetic patients. MJP Online Early 2:1–7 Zanon C, Brenner RE, Baptista MN, Vogel DL, Rubin M, Al-Darmaki FR, Gonçalves M, Heath PJ, Liao HY, Mackenzie CS, Topkaya N, Wade NG, Zlati A (2021) Examining the dimensionality, reliability, and invariance of the depression, anxiety, and stress scale–21 (DASS-21) across eight countries. Assessment 28(6):1531–1544. https://doi.org/10.1177/1073191119887449 Zhang CX, Chen YM, Chen WQ (2008) Association of psychosocial factors with anxiety and depressive symptoms in Chinese patients with type 2 diabetes. Diabetes Res Clin Pract 79(3):523–530. https://doi.org/10.1016/j.diabres.2007.10.014

Malaysian Rugby Team Coaching Competency: A Review of Qualitative Study Ahmad Fadzlee Ahmad Idriss, Mohar Kassim, and Ahmad Effendy Abdul Razak

Abstract This paper’s primary purpose of this qualitative study review was to define the changing in coaching competency environment of sports coaching professionalism. In current rugby coaching environment respond that presented thru coaching competency with relation existing peer-reviewed literature according sports coaching environments on the field in response to the scarcity of factual research. This is to provide an extensive framework for understanding current skill acquired and significance climax of coaching competency and offer a wider standpoint. Coaching practice has similar training process according to the standard policies applied by the international coaches which had a negative feeling or aggravate especially from the differential over cultural diversity according to the country and religion. While in Malaysia social incorporate activity always related with volunteerism which have existed on sports coaching tradition, currently it is improved by assisting the coaches to have certified accreditation with their professional training program. Benchmarked standards have been applied toward professionalism by producing standard system on formal sports coaching accreditation from the union as requirement for coaches handling the team on ground. This will increase coaching performance with more perspective on coaching competency with standardized solution on managing the team professionally. This paper focuses more on analytical direction performance toward sports coaching professionalization discourse. It scrutinizes the pressure and struggles that the coaches face during the training according to different phase and sector of sports. The progress on comprehension differences in sports coaching application is usually related to the coaching tradition that is socially used within the territory. While each sports coaching area requires additional exploration to increase understanding and scope that will benefit the research and analysis on coaching competency that become distant from another scope. Keywords Competencies · Team coaching · Accreditation · Professionalism A. F. A. Idriss (B) · M. Kassim · A. E. A. Razak Defence Fitness Academy, National Defence University of Malaysia, Kuala Lumpur, Malaysia e-mail: [email protected] M. Kassim e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_7

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1 Introduction Garrard (2021) states that the qualitative study review is to obtain the purpose, field, and specialization in making a systematic and critical reference on information and ideas related to the study’s title. The information obtained reviews from books, journals, and past research aimed at improving the understanding of the problems of the survey conducted for improvement and providing the best information. For foregoing 20 years, sports coaching discipline study scholars have researched numerous characteristics of coaching evolution and proficiency. The resulting frame of compositions narrated sports coaching as a compounded variety and diversity expertise and strength that takes years to mature. Specified large variety of resistance and efficiencies that coaches in sports anticipate to achieve, it astonishes from the coaching point of view from their reports that it is challenging on the field with high stress from the target that is being set (Fletcher and Scott 2010; Jones 2019; Olusoga et al. 2014). This review focuses on the early stages in rugby, mostly from the vista of coaching evolution in Malaysia, and how coaches are selected to be participants in knowledge enhancement training. Next, related to international and common concern, among the things explore include the character of coaches, coaching competency, coaching education, and coaching obstacle. The theme of this inclusion informs and provides a foundation for researchers on how to internally explore a particular issue contextually (Karim et al. 2020). The study results in conjunction with the key research in coaching proficiency focus on coaching competencies understanding, and coaching success within teams. The sports coaching evaluation focused on coach maturity on the following sub-concern; coach education, coach pathway, career expansion, and coach evolution stage (Karim and Ismail 2019). Mitchell and Tierney (2020) mention that World Rugby (WR) are the international governing body of the sport of rugby (and related games such as seven and 15 teams). WR is headquartered in Dublin, Ireland. WR, founded in 1886, organizes rugby sports activities worldwide and publishes laws and where games will run. As of February 2014, WR (before this is known as the International Rugby Board (I.R.B), the membership are 119 unions, for full members are 101 unions and 18 federated states. As stated by WR, rugby unions are played by both genders in more than 119 nations (Pike 2021). WR has the right to determine where the tournament and events being organized, except for the seven-team world championships in both category men and women, for which WR giving copy right to several international unions to obtain permission to organize the competitions. According to Renshaw et al. (2019) the social, economic, and technological changes in most countries result from a skilled workforce. Among the factors behind the change is the high-quality education system, especially teaching. These global changes also affect the coaching community, and developing high-quality coaching techniques is considered equally important. This is evidenced by the increase in coaching education programs and development programs conducted by the government, the sports, and higher education sectors. However, to produce quality teachers

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or educators in education, only a handful are aware of the need for “what should teachers know (lesson content knowledge) and what teachers can do (pedagogical and technical knowledge)?” (Renshaw et al. 2019). Researchers argue that the quality and delivery of training techniques are more of a concern in sports coaching because it requires detail in every training conducted. The sports coaching process progression that takes place on the field is often from the result of the skills and various tasks of coaching competency. Coaches have multiple responsibilities and duties within their position in developing their accreditation and approval. Karim et al. (2018) stated and related the coaches post as leaders, managers, instructor, teacher, counselor, consultants, performers, and mentor. According to Karim et al. (2019) coaching process necessitates interconnection of three basic shifting namely coach, players, and surroundings. This interaction process places coaching team at the center and becomes an integral part of the learning and training. This affirmation is brace by Siswanto et al. (2020), which view coaches as holistic problem solvers in planning, prioritization, contextualization, and cultivating in an ever-changing environment. Cropley et al. (2020) also state that the sports coaching process is related to community-based, lifestyle, and teaching practice built from interrelationships connecting teachers, students, training patterns, and contexts. According to Bradbury et al. (2020), coaching, in any form of training model is essentially a social education enterprise. Based on current practice, a coach is more of an expert in the subject matter (Kassim 2014). Coaches have diversification of management in an energetic collective environment and operate with restriction inside various organizational (Cassidy et al. 2008). Kassim (2008) stated that important responsible that all the coaches hold the pertinent accreditation and full responsible for practicing the coaching process. Expert trainers can operate effectively in specific contexts, make decisions, solve problems, and operate at a minimum level of ability as well as self-awareness (Kassim et al. 2019). Most coaching actions occur due to the detailed interlinkage of recognition and awareness of similar circumstances, by years of learning and deliberation (Wallis and Lambert 2021). Kassim and Mokhtar (2016) state that the scientific process of sports coaching compatible demonstrates the field of vision and coaching roles are very different and turn out to be progressively intricate. Sports coaches having occurring obstacle at the same time, to acquire the necessary coaching competencies, cover individual development needs, stay up to date and respond to industry basic requirement, meet coaching preceding demands, and eventually, have adequate self-awareness to acknowledge themselves by liaising constructively with the athletes under coaches’ supervision (Ramalu et al. 2020). According to Karim (2016), reinforcing sports coaching role competencies and proficiency are taking too much time on this learning evolution journey that may vary from that of coaches; ordinary coaching maturity on themes of obligation should be enlightening. Research on national coaches in this learning process will discuss important roles and responsibilities of sports coaching adaption from WR coaching competency Level 3 training and learning syllabus.

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2 World Rugby Coaching Competence Training and Learning Athletes of quality and a high level of performance are important assets in sports as well as sports coaches lead the way in guiding on high performance of sportsperson in sports. World Rugby (WR) through its training and education website according to Pritchard and Morgan (2022) states that rugby coaching competencies emphasize 5 components: planning, management and organization, observation and analysis, technical and technical applications, and communication and interaction. Jackson (2021) stated that sports coaching coaches play an influential character in improving the performance of an athlete according to their expertise and profession. An effective coach has the skills to be a motivator, teacher, counselor, and leader. Kao et al. (2020) stressed that coaches should ensure the effectiveness as well as the quality of the sport being cared for. According to Bompa and Buzzichelli (2014), a coach gains success by helping athletes improve adaptive skills in a variety of pre-applied tasks. The task of the athlete is also the development and mastery of basic skills up to the psychological, physical, technical, and even tactical preparation that is more specific to the understanding of the athlete especially at the high-performance level (Kao et al. 2020). Falcão et al. (2020) state that competitive advantage in sports is a source of increased coaching competence in every sport. Complex tasks to meet athlete achievement expectations require specific strategies and behaviors because they consist of a variety of variables. According to Pettit and Karageorghis (2020) coaching competence requires competence, ability, and fitness to carry out a given task. Kramers et al. (2020) showed that four types of skills and competencies that coaches must master in order to carry out coaching practice effectively are technical skills, conceptual skills, management skills, and interpersonal skills related to human relations. Previous research has stated the relationship between the importance and effectiveness of coaching with athlete achievement (Kassim 2008). Fung (2020) explained that these four dimensions provide the effectiveness of its use, namely motivation, strategy, technique, and personality of a coach. (i) Planning Planning and arrangement as likely are the major components for the coaches in preparing the best team. By making use of procedures based on methodological theory and knowledge, coaches can structure the training process in a way that authorizes athletes to increase their full potential performance at the precise time. The coach’s expertise to plan and execute the best training program effectively by having knowledge and experience on the field using training stimuli and skill training continuously. To help athletes reach goal-setting long-term training target, coaches must overseer athletes’ training preparation, at competition, and from time to time with specific measurement that can be used for data collection for comparing the players’ ongoing performance to maximize their potential (Kusuma et al. 2019).

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Depending on the specifics of the sport, it takes 6 to 14 years of devoted tutoring and full focus to produce an athletes great as possible for high-performance achievement. Heydari et al. (2021) stated that continuous training plan is an important element of the learning system as it drives athletes’ capability over the years related to sports activities. Training planning should be based on sports science and perfected through training. The execution scientifically structured training program reduces aimless practice and still work on un accreditation trainer which is still managing the team under sports association. (ii) Management & Organization In sports coaching, coaches’ achievement is carried out and focused on achieving improvement in competition starting from the district then national and lastly international levels. There are many factors in the athlete-building process that should be considered, including precise achievement objectives, a systematic training program, appropriate training materials, and methods. In addition, it is imperative to contemplate the quality of well-nurtured athletes physically and psychologically, resource capabilities and infrastructure facilities, and training planning conditions (Yunida et al. 2017). Sports management is a combination of organizational planning, leadership, control, budgeting, and evaluation skills that have key components related to highperformance sports (Keegan et al. 2020). High-performance sports organizations that are able to perform management responsibilities will also produce outstanding achievements. In sports management, team achievement must have explicit sports organization management and common goals in achieving overall organizational success (Sunarno 2018). The performance of a sports organization aims to develop athletes in a planned, scheduled, and systematic manner through competition to achieve achievement with the support of sports science and technology (Kusuma et al. 2019). The National Sports Council (NSC) Committee and the National Sports Institute (ISN) as national sports organizations are responsible for nurturing sports achievements in Malaysia. Sports science and technology support accompany various competitions to achieve planned achievements. High-performance core sports aim to achieve outstanding performance with good management and administration. Along with the increasingly intense competition in the world of international sports (Dixon et al. 2020). (iii) Observation & Analysis Observation is a popular technique that requires the coaching staff to be effective observers to identify athletes’ strengths and weaknesses in performance improvement (Mees et al. 2020). This is agreed upon by Leeder and Cushion (2020) by giving athletes a focal point where they may need to improve or work harder to achieve the best standards. Coaches and athletes meet to undergo an analysis that usually involves ways to improve by pointing out the athlete’s mistakes. Coaches provide feedback to athletes on how to improve performance so as not to commit the same offense again (Eather et al. 2020). Good coaches also work and strive indefinitely, using ways that

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can be used to lead discussions with the coaching staff (Peer Coaching) regularly (Logue et al. 2021). Observation refers to the undeviating keep track of the coach on the sports coaching surroundings. The main occasion on observations to allow coaches to take part directly lay out behavior feedback with athletes on training program such as modeling and adaptation (Kretlow and Bartholomew 2010; Neuman and Cunningham 2009; Stormont and Reinke 2012; Snyder et al. 2015; Khotimah and Ashadi 2020). Since observation is considered the best way to apply other coaching concepts, observation results are often studied in parallel with the development of athlete performance (Gholami et al. 2021). Heydari et al. (2021) stated that observation performance analysis divides competitions, proficiency, capability, expertise, etc., into measurable components or tournaments. Justification to recognize weaknesses toward athlete or team and starting point for the error that originates toward the defective team capabilities. The substantial obstacle in high-performance sports coaching analysis is learning and adjustment data that can be seen as an activity that helps improve teams for constructive purposes and improves the performance of individual athletes. Hananto (2020) supports this by stating that although the use of high-performance data analysis is important to improve apprehension on high-performance sports coaching, it should be remembered that in professional sports background, differentiate from the academic learning process thru the books and research process, data analysis study usually to improve future sports performance. The improvement to rectify problem on game performance correction just a few hours or days during the tournament. (iv) Technical & Tactical Applications The elements that differentiate various sports activities are the techniques (i.e., motor skills) as well as the tactics involved. Athletes’ ability incorporated all the mechanisms on skill, technical, tactical, and game specification mastery needed to be at their best to perform in playing the sports. Technique can be contemplation way of bringing about a skill or somatic exertion. The impeccable technique creation on most suitable movement patterns from athletes must be retained from full commitment and weightage on training ground. Each sports venture has a technical standard or model that is embraced as perfection or practically close to perfecting and portraying sports-specific performance configuration. Sports-specific models must recognize appropriate and show beyond doubt effectiveness to be widely accepted. Tactical should show some flexibility as they always need to be notified and apprised based on latest exploration analysis. The study can assist coaches using tactical as a point of comparison for athlete high-performance training. Coaches can generate training program for targeted skill and team pattern plan based on the athlete’s game analysis data. While this technical pattern is crucial on arrangement tutelage impetus, nevertheless athletes are likely to reinforce their personal performance tactical design. The structure of training is no different, but athletes can make the skill look different because of its distinctive presentation style and adaptation. In team sports, the application of high-performance models is very specific to the team and relates to the skill set or team performance. Presentation style can have

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tactical implications and can influence how a team conducts technical and tactical preparation. (v) Communication & Interaction Communication is to demonstrate the pose on (or disseminating) proposal, point, conceptualization, opinion, and thought, usually perception of what is indicated by others (Chatterjee et al. 2021). Choi et al. (2020) agreed that necessitating on sending and receiving of messages are consequential conveying processes and can get hold of many incarnations. Oral transmission is spoken words, while non-verbal statement implies anatomy posture, effort, facial countenance, and action. This requires not only the information of the verbal data but also its psychological impact, or the impact of that content on the person receiving it (Milius et al. 2020). In addition to interacting with team management, a coach must be an active liaison with his athletes in order to be an effective leader (Gomes et al. 2020). The capability to be in touch is an essential element for being a positive functioning coach and producing high-performing athletes. Two entities’ exchanging formal orders is the method of conveying in the same manner using one or more communication instruments. Sosiawan and Saptono (2020) explain this is the foundation on which coaches build their teams. Successful communication is frequently recognized as triumph on essential segment of high-performance sports coaching and athletes. Each squad member must study how to deal with all teammates inside and outside the training and competition ground to increase their togetherness and team bonding. (Wachsmuth and Jowett 2020).

3 Methods Hermawan (2019) states that the intrinsic research specialization was selected for the current case study because this research offers the potential to gain access to rich data sources and an in-depth understanding related to the coaching ranks of the Malaysian national rugby team. The subjects of this study consisted of the coaches of the Malaysian national rugby teams (n = 6) involved in this study which were two 15’s a-side rugby team, two 7’s a-side man team, and two 7’s a-side women team. The coaching staff was selected not only based on the ease of access to the team but the study conducted, the research should conduct the study with a very strict time estimate especially in the period of silence as well as relatively minimal meeting access. Therefore, the coaching line is considered as an example and appropriate research representatives are conducted in Malaysia to obtain the findings of detailed research data that can help improve the performance of national coaching in the future. Scientific methodology is a very important component on methods consciousness used in the compilation of research-based documents, for example, manuscripts, dissertations, or papers solving the learning research objectives in the university (Fatmawati 2020). According to Creswell (2015); Lebar (2014), the qualitative

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methodology allowed interview to get rich descriptive data. Researcher wants clear understanding for the sports coaching guideline and information regarding commitment in coaching competency to understand requirement in choosing qualitative methodology and open-ended interview. Grounded theory analysis configuration on the data gathered from the national coaches concludes qualitative methodology approach to help the study research. The objective of the qualitative methodology is to produce information that provides a clearer understanding and illustration to understand the various dimensions of the problem being analyzed. Researchers discuss several things related to the research methodology to find out the level of competence of rugby coaching in Malaysia. The research method conducted is qualitative in nature that uses a case study approach because it is compatible with the researcher’s experience in the sport of rugby making it more concrete and easier to understand (Lebar 2014). Typically, case studies integrate all aspects of research: theoretical and empirical information that sustains work, life experiences, and results obtained are analyzed in the thesis (Samsudin and Awang 2021). Othman Lebar also stated that case studies can give researchers the advantage of exploring and making interpretations to gain a more detailed and flexible understanding, especially research on sports coaching. This research conceptual framework aims to respond on the research questions based on sports coaching and review the available literature on the knowledge and behavior of national coaches. There are six Malaysian national coaches which undergoing rugby training for the national team appointed by Malaysian Rugby. Conceptual and theoretical discussions that take place can explain the significance on coach’s knowledge and behavior and its impact on training planning as well as player performance (Ryan and Duckworth 2020). In order to attain the research objectives, this study comprises a factual scanning of the views of the Malaysian rugby national coaches. Taking a more holistic approach to research understanding, stated from Sarkar and Hilton (2020) essentially the concept of flexibility with directing characteristics and interview uniformity is emphasized. Head coach is the decision-maker in intriguing every rugby high-performance plan of action for three group of national team consisting of 15’s a-side man, 7’s a-side man, and 7’s a-side women, and participants are all the current national coaches. Interviews with head coaches and assistant coaches used in-depth semi-structured interviews to build a qualitative basis for the formation of ethnographic survey studies, researchers observed the behavior and reactions of the coaches during the interviews. In addition to interviewing Malaysian national rugby coaches and analyzing transcript document also conducted in understanding the key component on the coaching accreditation that influence the recognition of Malaysian rugby national coaches. Theoretical purposive sampling is used to choose the selected participant so that constant differentiation on new data collected from the preceding data gathered on conceptual data compendium. Researcher decided that in-depth semi-structured data collection interview with an open-ended question format be scheduled until theoretical saturation of information is reached (Patton 2015). According to Harvey et al. (2020) qualitative can relate on subjective evaluation and description. Identification

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competency element in rugby coaching system as well as a description of the components in non-numerical terms. Validity certification content from the interviewer is carried out according to guideline qualitative analysis procedure Sarmento et al. (2014). Karatas (2020) explains that epistemology is concerned regarding nature and scope on knowledge contemplate individual stance on learning with confirming understanding the distinction between opinion and belief. Important to answer question on mastery the source on awareness how it is acquired and how we answer the question of what we know. In connection with this study, these problems need to be discussed, debated, and understood because as shown by Vardarlier and Özsürünç (2019) that study has proven that knowledge can provide a basis cognition on how coaches utilize their areas of proficiency in practical environments (e.g., sports coaching). Explanation by Kérivel et al. (2021), in qualitative exploration the main research instrument is the researcher, and the researcher’s idea is the principal force for conducting the dissection. All data contributors were well informed regarding the study conducted and everyone agreed with the term data protection from the research conducted and the contribution they devote for academic purposes by signing the consent form. Interviews’ duration from 75 until 111 min was assembled, and the data collected from digital file recorded using iPhone 12 Pro Max was later put in writing verbatim to be analyzed according to evolved grounded theory (Corbin and Strauss 2015). Qualitative research is based that we understand the world around us based on the individual values and experiences we acquire, and therefore everyone has different interpretations of events in their lives, and sometimes shares events, in different ways (Aoyagi et al. 2020). The researcher is using Atlas TI v22 to get more insight and understanding relation between theoretical sampling process from the coding and facts contribution and to expend a combine data-compel hypothesis using researcher experience as a qualified coach (Hermawan 2019) it aims to gather a deep understanding of human behavior, treat each individual decision and its uniqueness equally important in advancing our understanding of expertise of interest to find the best results of how coaches believe that their performance should be evaluated.

4 Results Athletes of quality and have a high level of performance are important assets in sports as well as responsible of high-performance coaches guiding their athletes in sports. There are six problems on key competency that emerged from the interview done with all the national coaches (1) understand coaching competency, (2) challenges on coaching competency, (3) athletes adjustment, (4) athletes training data collection, (5) understanding sports psychology, and (6) training center with hightech equipment. Jackson (2021) stated that studies on sports coaching play major character improvement on the performance of an athlete according to their expertise

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and profession. An effective coach has the skills to be a motivator, teacher, counselor, and leader. Kao et al. (2020) stressed that coaches should ensure the effectiveness as well as quality of the sport being cared for. According to Bompa and Buzzichelli (2014), a coach gains success by helping athletes improve adaptive skills in a variety of preapplied tasks. The task of the athlete is also the development and mastery of basic skills up to the psychological, physical, technical, and even tactical preparation that is more specific to the understanding of the athlete especially at the high-performance level. This can have a significant impact on well-being as well as understanding that can improve the performance of athletes with the functions demonstrated by the coaching ranks (Kao et al. 2020). (1) Understanding coaching competency According to Light (2013) Coaching competency approach has a complex learning understanding from theory perspective because of the instructional approach and behavior views in learning mechanism. Usually, coaches will determine the level of target to be achieved during training according to planning that is being done earlier with the team. The player’s achievement must be implemented accordingly with the training program so that players have the effort to reach the target set by the coaches. According to MC1, “The level of understanding on coaching competence skill between coaches also different with the skill come from the experiences and knowledge of the coach”. Coaches also need to differentiate the talent from all the players because players came from different background and exposure. Coaching competency is also different according to ability to give instruction and ability to manage program related to players’ skill development during training and tournament. Lastly is how the coaches need to adapt the environment and the material available in developing players’ strength for the team high-performance development. (2) Challenges on coaching competencies Kao et al. (2020) based on understanding of coaching competency among all the national coach in Malaysian Rugby showed different levels. The more senior coaches show more superiority than other junior coaches because they are more likely to use their experiences gained with more game time and exposure during tournaments. MC3 stated that “usually all the coaches will adapt according to their experiences gained during their time representing the country and change according to the team needs and competition on what to be improved on the training program for international level”. Jackson (2021) stated that in contrast to the younger coaches they can be defined as competent in skill by seeking more details in term of knowledge that is more practical with the high-performance training concept with latest information gain from courses and ongoing education. This is why the existing coaching competency gaps to be bridged to create a better program for the national team to improve team preparation on high performance.

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(3) Player’s adjustment Edwards et al. (2021) stated that coaches can always keep track on how their players respond during training session by the way they eat, sleep, think and even when stress out during decision-making based on information and observation. The results will differentiate between losing and winning. CM4 agreed that “player’s analysis is important for coaches understanding with all their players to lead the team toward success”. Consistent on coaching competency had long been used on assessment players by evaluating behavioral action. Researcher found that all coaches face problem during training on adjustment for the players’ planned training pattern that is designed according with high performance and more practical. Coaching competency can easily be used to identify players’ strength and weaknesses on the training program that suit with the national team (Edwards et al. 2021) with adjustment from the players’ adaptation on following the program provided. (4) Player’s data collection This is aimed specifically at coaches by Amayo and Tierney (2020) who may not be able to get the help of a local rugby club or national rugby union, especially in terms of players’ data collection during training and competition. CM5 emphasizes that “every coaches have their own way of understanding in collecting data from each players from the first day they started joining the camp or centralize training until the competition on players progression and improvement”. Coaches must have good insight on their players to analyzing on players result from the data findings. This can assist coaches to diagnose the failure in a program and plan and restructure the best program that players can adapt with the analysis and data gathered. Analyzing all players must start from the beginning they entered the program until the end of the tournaments (Rothwell et al. 2020a, b). (5) Understanding Sports Psychology Sports psychology knowledge and skill from Hermawan (2019) perspective is to resolve the optimal performance and increase confident of athletes in developing mental toughest for sports participation in getting better result. However, Sebbens et al. (2016) stated that coaches often find this topic intimidating and therefore place it on expertise component. According to CM5 and CM2 in this research stated “handling and leading the national rugby team as a coach, we have to do multi-tasking on and off the field where players will refer all sorts of problem regarding family, lover and even life style”. Consistent with the statement of Ohuruogu et al. (2016), psychological knowledge is important to coaches at all levels. Coaches will have more understanding the psychological impact on players’ behaviors in the team and decision-making during competition. (6) Training center with high-tech equipment One of the biggest challenges coaches faces with current data analysis is their reliance on human memory and vision that always have less impact with the modern days’ sports coaching. Based on Law et al. (2018), technology has played big impact toward

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sports coaching preparation to improve players’ capability in high-performance environment. High-tech equipment is more comprehensive and much more effective with the information given to increase players’ performance. High-tech tools and technologies such as monitor and portable video camera with instant playback technology have made analysis easier to decipher, and future plan can be made instantly. CM6 justifies that “problem arises for the national team because we need expert guidance and it is too expensive due to high owning cost, maintenance and interpreting data. It is difficult with less support from the governing body and also private sponsorship”. Joncheray (2021) stated that regarding coaching competencies the consensus and expressions required to be part of the coaching staff differ from capacities and capabilities. Study on sports coaching reveals view and understanding from coaching panorama on the ground by using different approaches and planning toward athletes’ high-performance planning and preparation. Joncheray also stated that descriptions of proficiency, ability, and potential have a major role on sports coaching performance and coaches’ ability as a creative composition on the field. Application sports coaching processes have shown substantial impact toward high-performance athlete planning. Combination coaching experience and academic research have displayed more understanding toward athletes’ periodization and peak performance. Sharing responsibility on arrangement and specification training with support personal creates grandiose high-performance team cohesion toward competition. Teamwork between management and coaching team will produce more effective execution and implementation toward high-performance team and athletes preparation.

5 Conclusion According to source of this coaching manual kit, it has always been emphasized that the involvement of local, national, and international rugby organizations should be studied in team training activities, especially in terms of rugby coaching competencies. Morgan et al. (2020) argued that getting the appropriate resources such as coaching manual guidance in Bahasa Melayu, best clothing material for competition, latest training equipment such as rugby balls, training equipment, and fitness training tool is difficult because it is so expensive. The involvement of Malaysian Rugby Union is addressed in more detail in the coaching module mobilizing the community as well as rugby partners in Malaysia (Winkelman 2021). In Malaysia applying sports science mainly sports coaching study for preparing high-performance team are very new and inexperienced. Adaptation must be made toward the national team especially the union in preparing and updating all national coaches to understand and use all the support and expertise from the previous research that has been done to get the maximum outcome from the athletes to compete and adjust with the modern game team preparation. The study suggests that stakeholders provide continuous training so that competencies can be maintained and improved, especially aspects of specific competencies.

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As a sharing of experience in developing a competency model, this research is written to comprehensively discuss the concepts, principles, and guidelines used in developing the model. According to Putra and Hizatul (2004), this competency model is expected to provide insight into the extent of process accuracy taken, the validity of observations and conclusions made, as well as the extent to which the model addresses performance issues. All categories of competencies are important to an individual in performing a task. Skills and knowledge are very important in task execution (Salgado and Berntsen 2019). Collectively, study on sports coaching education establishes coach as coordinators’ obligation to acknowledge how coaches proceed by dint of development phase to apprise top practices, and high-performance preparation (Brown et al. 2019). This statement is supported by Thelwell and Dicks (2020) who express that in the surroundings of sports, concepts with conceptual examinations on this level are quite limited as well as inadequate, especially in societies or new levels across the issuefilled spectrum as it affects coaching team. Usually, there will be miss information or different opinion between on-ground coaches and academic researchers, despite the fact that this is cautiously being addressed (Jones 2019). Additional observation on coaching high-performance planning to be implemented which needed to enlarge employment pathways for coaches, need to work out techniques and ways of information about how coaches develop and experience the transition process (Thelwell and Dicks 2020). Developmental on specific juncture in the formative sports coaching procedure have been identified (Renshaw et al. 2019) such as outlining phase of maturity can be divided into quartet stages of (a) apprentice, (b) proficient, (c) qualified, and (d) specialist. Beginner coaching staff with not as much as three years of experience will be more anxious about imparting knowledge and more concern about athlete’s functioning. With practical knowledge, the coach begins to reinforce skills that allow to reduce time stretch on non-coaching chore, devoting ample time refining training program toward player preparation (Wilkinson and Grecic 2019). Coaching efficiency can be related when the coach can use precursory experience to resolve problems based on new game situations. Based on the vast knowledge and experience acquired, skilled coaches can differentiate important or non-important issues (Butler 2020). Coaches tend to respond with less use of rational thinking and rely on ability and divination. Coaching team usually feel accountable for the success or failure of their athletes. High-performance coaching position and the distinguishing feature of a coach’s priorities are that intuition and automatic reflexes are often used in decision-making (Carson et al. 2018). Key points • This study is to examine Malaysian national coaching competency program during attachment with the Malaysian Rugby Team. National coaches give their personal perception in qualitative concept from their experience during coaching the national team. • Study provides a new perspective in Malaysian rugby coaching team in performing and maintaining competency during handling the national team.

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• Training and education from World Rugby module will be the guideline for the national coaches to maintain the coaching competency during training and team preparation.

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Association between Obesity Risk Knowledge and Body Mass Index among Sport Students Alya Natasha Rozzaini, Farhanah Abdul Rahman, Nur Asmidar A. Halim, and Noor Fatihah Ilias

Abstract Knowledge about the health risks of obesity is crucial in motivating a person to practice a healthier lifestyle and aid in preventing adverse health effects of non-communicable diseases (NCD) caused by obesity. However, the association between knowledge and obesity rate among students was inconclusive. Therefore, this study aimed to determine the relationship between the knowledge of the risk of obesity and body mass index (BMI) among Sports Science and Recreation (FSR) students. The correlational study involved n = 436 students from FSR. The obesity risk knowledge-10 scale (ORK-10) questionnaire was used to measure the level of knowledge on the risk of obesity, and BMI was used as an indicator of the obesity rate. A total of 257 (58.9%) male and 189 (43.3%) female students participated voluntarily in this study, with a minimum ORK score of 0, and the maximum score was 10. The results showed that the mean score for knowledge was 4.77 ± 1.60, and the mean for BMI was 22.77 ± 4.14. There was no association between knowledge of the risk of obesity and obesity rate among sports students, r (436) = 0.003, p > 0.05. These results showed that the students had poor knowledge of the risk of obesity but a normal BMI. Thus, knowledge of the risk of obesity does not influence the obesity rate among sports students. Keywords Obesity risk knowledge · Body mass index · Sports science students

1 Introduction Obesity has become a concerning matter as its prevalence has increased in most parts of the world. As of the most recent findings, there are more than 650 million obese adults worldwide (Haththotuwa et al. 2020). The prevalence increased from 100 million in 1975 to 671 million in 2016 (Abarca-Gómez et al. 2017). Based on this figure, it is about 571 million increments in the number of cases in the past 41 years, A. N. Rozzaini · F. A. Rahman · N. A. A. Halim · N. F. Ilias (B) Faculty of Sports Science and Recreation, UiTM Shah Alam, Shah Alam, Selangor, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_8

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with about 14 million patients each year. The increasing trend in the prevalence is forever a concern in this matter. Malaysia is one of the countries that should be worried about this situation. The prevalence of obesity among Malaysian adults has increased over the past ten years (Zaki et al. 2018). The increasing prevalence of obesity problem continues, and university students are also affected. Peltzer et al. (2014) reported a high prevalence of overweight or obesity among university students from 22 countries. Therefore, the obesity prevalence was high, and the trend in the prevalence was also increasing as reported globally. There are a lot of detrimental effects caused by obesity toward the person that suffers from being obese. Obesity is the cause of the development of chronic diseases, the risk of comorbidities, and premature death (Bray et al. 2017; Jastreboff et al. 2019). Cardiovascular disease, cancer, the development of type 2 diabetes mellitus, hypertension, and osteoarthritis are some of the non-communicable diseases (NCD) caused by obesity (Malone and Hansen 2019). In addition, obesity is strongly associated with the development of cardiovascular diseases (CVD) (Battineni et al. 2021). Besides that, obesity affects students by reducing their academic performance (Jastreboff et al. 2019). Anderson and Good (2017) found an association between higher BMI with lower college academic performance. Therefore, obesity causes many adverse health effects and is responsible for reducing the quality of life of an individual. Moreover, obesity as well affects student’s academic attainment. As the prevalence of obesity increases and the consequence is troublesome, the need for preventive strategies becomes essential. According to Zabia and Chua (2020), preventative methods are significant in reducing the obesity rate in Malaysia. A healthy lifestyle, including a healthy diet and regular physical activity, is crucial in obesity prevention. Physical activity, healthy dietary fats, high dietary fiber, and less processed and sugary foods were found to help maintain weight loss and lower the risk of obesity (Alexander et al. 2022). Another crucial preventive method is increasing the knowledge of the risk of obesity. Kan and Tsai (2004) stated that an individual could be prevented from becoming obese with the possession of knowledge about obesity health risks. Oyewande et al. (2019) also reported that knowledge of obesity might reduce the risk of obesity among adults. Knowing the risk of being obese, an individual may implement preventive measures like exercise and/or dietary control (Kan and Tsai 2004). Thus, obesity can be prevented with the practice of a healthy lifestyle and by making the possession of obesity risk knowledge the main priority. Many studies have been conducted to find the association between knowledge and the obesity rate. A recent study by Oyewande et al. (2019) showed an association between knowledge and the obesity rate. For those knowledgeable about the risk of obesity, the body fatness was normal, and those with low knowledge tended to become obese. However, a study by Ghazi et al. (2018) reported no association between these two variables. Those with high knowledge were said to be obese, and those with low knowledge had normal body fatness. This shows that there was an inconclusive finding. Behavioral assumption is closely related to reality (Kan and Tsai 2004). Since sports students were also trained to become exercise therapists, knowledge of the risk of obesity is essential. This knowledge may encourage obese patients

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to seek help from exercise therapists to manage their obesity problem. However, practitioners whose careers emphasize research or clinical management of obesity showed extreme weight bias (Schwartz et al. 2003). Besides, weight bias among students and professionals in exercise science, physical education, kinesiology, and fitness instructor has not been extensively reviewed (Zaroubi et al. 2021). Therefore, this study aimed to determine the association between the knowledge on the risk of obesity and BMI among sports students.

2 Method 2.1 Study Population A total of 436 students from the Faculty of Sport Science and Recreation, UiTM Shah Alam, were recruited. The inclusion criteria consisted of registered Sport Science (SR243) and Sport Management (SR241) students from the Faculty of Sport Science and Recreation UiTM Shah Alam, aged 20–26 years old, full-time students, and able to read and understand the English language. All the subjects were free to participate and informed regarding the methodology and benefit of the research. This research was approved by the UiTM ethics committee: 600-TNCPI (5/1/6).

2.2 Data Collection Procedure The design used in this study was a descriptive correlation design using a selfadministrative questionnaire to identify the relationship between knowledge on the risk of obesity and body mass index among FSR students. To evaluate the subject’s knowledge on the risk of obesity, the ORK-10 questionnaire was used. Self-reported body weight and height were used to calculate the body mass index due to COVID19 restrictions. Data were collected online using google forms; respondents were invited using WhatsApp applications and email to self-answer the online survey. Researchers provide the subject with the contact number for further clarification if needed. The google form was shared among students in the Faculty of Sport Science and Recreation Shah Alam only. Google form consists of three sections. First, subjects were given general information about this study which were the benefit and procedures of this study. Then, subjects were given informed consent, informed that they were free to join or no penalty would be given if they refused to join. Then, subjects fill up body weight and height data and are directed to a questionnaire.

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2.3 Obesity Risk Knowledge-10 (ORK-10) Questionnaire The obesity risk knowledge-10 (ORK-10) scale consists of a 10-item questionnaire that assesses knowledge of obesity-related health risks. The overall scale’s Cronbach’s alpha was > 0.7 (Swift et al. 2006). This self-completion requires the students to judge the statement as either ‘true’ or ‘false’ and ‘don’t know’ for uncertainty about the statement. One point was given for the correct answer, and zero points were given for incorrect and uncertain answers. Thus, the minimum score can be achieved as zero, and the maximum is 10. Those who answered five or more questions correctly were considered high knowledge, whereas those who correctly answered less than five questions were low knowledge (Alasmari et al. 2017). The higher the score indicates good knowledge, and the lower the score indicates poor knowledge.

2.4 Statistical Analysis Data were analyzed using statistical package for social sciences (SPSS 2.0). Descriptive analysis was used to describe the demographic data. Pearson’s correlation was used to identify the association between ORK score and BMI. All data were presented in mean and standard deviation with a significant level set at p < 0.05.

3 Result A total of 436 students were enrolled in this survey (mean age 21.85 ± 1.31 years). The characteristics of the subjects are listed in Table 1. This study consisted of sports science (n = 256) and sport management (n = 180) departments from the Faculty of Sports Science and Recreation (FSR) Shah Alam. Overall, more than 50% of sports students had good knowledge on the risk of obesity (n = 247, 56.7%), and 189 (43.3%) sports students had low knowledge on the risk of obesity. Besides, sport students were generally had normal BMI (n = 271, 62.2%), overweight (n = 80, 18.3%), and obese (n = 33, 7.6%). The mean score for knowledge of obesity among sports students was 4.77 ± 1.60, and BMI was 22.77 ± 4.39, respectively. Table 2 showed that there was no association r (436) = 0.003, p > 0.05 between knowledge of risk of obesity and obesity rate among sport students. Knowledge on risk of obesity does not affect BMI among sports students.

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Table 1 Subject characteristic Variables

Minimum (Min)

Maximum (Max)

Number of subjects

Frequency (n)

Percentage (%)

Mean (SD)

436

Departments Sports science department

256

58.7

Sports management department

180

41.3

Male

257

58.9

Female

179

41.1

Age

18

26

Gender

Knowledge on risk of obesity

0

10

4.77 (1.60)

High knowledge

247

56.7

Low knowledge

189

43.3

Body mass index

14.8

36.2

22.77 (4.39)

Underweight

52

11.9

Normal BMI

271

62.2

Overweight

80

18.3

Obese

33

7.6

Table 2 Correlation between knowledge on risk of obesity and BMI

Variables

Correlation

P value

ORK-10 scale and BMI

0.003

0.948

4 Discussion This study focused on young university students as they are the future leader of a country. As a future leaders, for them to be in the best state of health and wellness is important to ensure greater longevity. According to American College of Sports Medicine (2013), obesity may lead to non-communicable disease and musculoskeletal disease and increase the risk of disability. One of the strategies to minimize the development of NCD’S is by preventing obesity. Obesity can be minimized by enhancing the knowledge on risk of obesity. As reported by Oyewande et al. (2019),

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knowledge on risk of obesity may reduce the risk of obesity among adults. Accordingly, the possession of knowledge on the obesity’s health risk prevents an individual from being overweight and obese (Kan and Tsai 2004). Hence, by improving the knowledge on risk of obesity among sport students, it may reduce the number of obesity and indirectly be able to become a sports leader in future. Table 1 showed 56.7% sport students had high knowledge on risk of obesity according to the ORK-10 scale results. This could be indicated that half of sport students are aware about the factors that contribute to obesity. Meanwhile, low knowledge on risk of obesity is also considered high among sports students. Surprisingly, the mean score for knowledge on risk of obesity among sports students was 4.77 ± 1.60 (Table 1). According to Alasmari et al. (2017) if the ORK-10 score is less than 5 over 10, it is considered as a poor awareness on risk of obesity and vice versa. Therefore, it can be concluded, and knowledge of the sports students regarding risk of obesity was generally poor. Study by Oyewande et al. (2019) found the same result where students had poor knowledge on risk of obesity. Besides, a study by Ghazi et al. (2018) reported poor knowledge on risk of obesity among students in Malaysia. Possibly, the main factor that could lead to poor knowledge on risk of obesity among young sports students is related to high levels of physical activity. Sports students were generally physically active (Noor Hamidi et al. 2021) that indirectly they had an ideal body weight. Probably due to an ideal body weight, sports students did not concentrate much on the knowledge of risk of obesity. Study by Sirico et al. (2018) reported higher physical activity levels may lower the risk of being obese. Hence, probably, higher physical activity levels could be the reason, and sport students had poor knowledge on risk of obesity. Result of this study on obesity rate based on BMI showed sports students had an ideal body weight. In overall, the mean score for BMI among sports students was 22.77 ± 4.39 (Table 1). This finding showed a low prevalence of obesity among sports students. Table 2 showed the majority, 62.2% of sport students had normal BMI, 11.9% were underweight, 18.3% were overweight, and 7.6% were obese. This finding is similar as per discussed above where sports students were physically active; therefore, they had ideal body weight. According to Hemmingsson and Ekelund (2007), most studies indicate an inverse relationship between physical activity and body mass index. This means a lower obesity rate among physically active individuals. A higher physical level could result in a lower obesity rate. However, it is about 25.9% of sports students had abnormal body weight which there are overweight and obese. This could be explained perhaps due to sports students having larger muscle size and mass, therefore increasing the body weight that is probably the result of abnormal body weight. BMI has failed to distinguish between lean and fat mass among active individuals (Okorodudu et al. 2010). Results of this study showed that there was no association r (436) = 0.003, p > 0.05 between knowledge of risk of obesity and obesity rate among sport students. It is indicated knowledge on risk of obesity does not influence the obesity rate among sport students. This could be explained by the finding of this study, where sports students had poor knowledge on risk of obesity; nevertheless, they had normal body mass index. Similar study reported that knowledge on risk of obesity does not influence

Association between Obesity Risk Knowledge and Body Mass Index … Table 3 Sub-analysis on risk of obesity and BMI

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Variables

Frequency (n)

Percentage (%)

Low knowledge, normal BMI

114

26

75

17

157

36

90

21

Low knowledge, abnormal BMI High knowledge, normal BMI High knowledge, abnormal BMI

the obesity rate (Alasmari et al. 2017; Kan and Tsai 2004). This resulted possibly due to many other factors that could lead to obesity such as eating style, sedentary lifestyle, and genetics. Obesity is highly related to environmental, socioeconomic status, genetic factors, dietary factors, physical inactivity, hormone imbalance, and stress (Milagro et al. 2013). Therefore, knowledge on the risk of obesity alone did not provide an association to reduce the number of obesity cases among sport students. No association between knowledge on risk of obesity and BMI score among sports students can be explained thru sub-analysis data. No association between these two variables was provide four outcomes. First, sport students had low knowledge but normal BMI. Second, sport students had low knowledge and abnormal BMI. Third, sport students had high knowledge and normal BMI. Last, sport students had high knowledge but abnormal BMI. Table 3 showed the percentage for the four outcomes which is relatively the same. Sub-analysis was conducted, where abnormal BMI score was considered those who in category of underweight, overweight, and obese. 21% of sport students had high knowledge on risk of obesity, but they had poor BMI score. Those who had high knowledge on risk of obesity nonetheless abnormal BMI category probably due to time constraints to be physically active. Probably, sports students are aware of the risk of obesity, but due to time limitations that lead to sedentary lifestyle, and indirectly lead to higher BMI score. As reported by Arzu et al. (2006), the main factors that resulted in physical inactivity among students were due to not having enough time to do exercise. Therefore, some sports students have a good knowledge on risk of obesity, and they are not able to participate actively in physical activity; hence, higher BMI score. Next, sports students had lower knowledge on risk of obesity, but they had good BMI scores. Sub-analysis was conducted, 26% of sport students had low knowledge on risk of obesity, but they had normal BMI score. Possibly, those who had low knowledge on risk of obesity but normal BMI category probably due to consent much on body image. Young people somehow prefer to look good; therefore, they consent to their body size. Study by Millstein et al. (2008) higher body mass index was significantly associated with body size dissatisfaction. Younger age consent much on body image as they may feel disappointed when they were obese; therefore, they had significant association with lifestyle changing behavior (Zelenyt˙e et al. 2021).

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Therefore, even sports students had a poor knowledge on risk of obesity, but they consented more on body image, eventually leading to a normal BMI score. Another factor that could explain no association between knowledge on risk of obesity and BMI among sport students is the syllabus content which is sport course. Sub-analysis was conducted, 36% of sport students had high knowledge on risk of obesity, and they had good BMI scores. Syllabus in the sport science course is related to exercise as a preventive tool to overcome obesity, it indirectly helps students to have normal body weight (Richardson et al. 2015). Therefore, this may predispose them to a narrow lens regarding the benefit of physical activity on health outcomes. It seems knowledge on risk of obesity provides an insight to have a good BMI score. Besides, low knowledge on risk of obesity may result in a poor BMI score. Based on a sub-analysis conducted, 17% sport students had poor knowledge on risk of obesity, and they had poor BMI scores. Weight bias among sport students is generally exist where some sport students having the poor knowledge and they are physically obese. This is alarming, where exercise therapist who is responsible for management of obesity cases was obese. This result may lead to obese patients reluctant to seek health care. Future weight bias reduction interventions should be designed to address this issue. Obesity rate among sport students can be influenced by many factors such as time constrain to exercise, body image, and syllabus content. Due to many aspects that could lead to obesity, knowledge alone does not seem influence much on obesity among sports students. Actively participating in physical activity is the most effective approach for reducing obesity (Talarico and Janssen 2018). Taken together, enrichments on knowledge of risk of obesity together with any other factors such as exercise intervention possibly may resulted to be promising strategies for reducing obesity rate. Knowledge on risk of obesity does not influence BMI score among sports students, but possibly knowledge on risk of obesity may provide significant effect on BMI score among obese students. This possibly due to sport students are physically active, indirectly normalize the BMI score. Therefore, further study focuses on obese student which is granted to highlight the importance of knowledge in reduce the obesity rate among students. To summarize, this study found that sports students had poor knowledge on risk of obesity. However, the prevalence of obesity among them was reported to be low. This result suggests that such a relationship does not exist among sports students. Acknowledgements The author sincerely acknowledges Faculty of Sports Science and Recreation for providing support to conduct this research. The author thanks Alya Natasha Rozzaini, Farhanah Abdul Rahim, and Nur Asmidar A. Halim for great contribution to complete this research.

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High-Intensity Interval Training Protocols Variation Response to Immune Parameters and Cardiovascular Risk Factors: A Scoping Review Nik Siti Nik Zaid, Ayu S. Muhamad, Mohd Nidzam Jawis, Foong Kiew Ooi, Mahaneem Mohamed, Rohimah Mohamud, and Normah Jusoh Abstract High-intensity interval training (HIIT) is a form of interval training alternating short periods of intense anaerobic exercise with less intense recovery intervals. HIIT has gained much attention around the world as a method to reduce time commitment for exercising which minimize the barrier of being physically inactive. In addition, various research reported that HIIT produced similar benefits to traditional exercise in improving health status as little as two weeks. There are various protocols of HIIT such as Power 90 Extreme (P90X), Tabata, Spinning, ISANITY, CrossFit, and Sprint 8. However, the findings on which HIIT protocols offer the most effective methods in the role of improving immune system and inhibiting cardiovascular disease (CVD) development are not well explained. It is also uncertain on which protocols, type of exercise movements, duration and volume constitute optimal training for inducing the desired change in immune function and CVD risk factors. The main aim on this study is to provide a brief summary of the current literature regarding the HIIT protocols variation through the immune functional perspectives and its role in decreasing the risk of CVD risk factors. Keywords HIIT · High intensity · Immune response · Cardiovascular disease

N. S. N. Zaid · A. S. Muhamad (B) · M. N. Jawis · F. K. Ooi Exercise and Sports Science Programme, School of Health Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian, 16150 Kelantan, Malaysia e-mail: [email protected] M. Mohamed Physiology Department, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian, 16150 Kelantan, Malaysia R. Mohamud Immunology Department, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian, 16150 Kelantan, Malaysia N. Jusoh Faculty of Sports Science and Coaching, Coaching Science Department, Sultan Idris Education University, Tanjung Malim, Perak, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_9

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1 Introduction High-intensity interval training (HIIT) consists of a few sets of high-intensity exercises, immediately followed by recovery periods (Driver 2012). The period interval of high-intensity exercise may range anywhere from 5 or 10 s to 5 or 10 min. Likewise, the period interval of recovery may vary in duration (Driver 2012). There are various protocols of HIIT such as Power 90 Extreme (P90X) (Woldt 2011), Tabata (2019), Spinning (Kang et al. 2005), ISANITY (Virgil et al. 2020), CrossFit (Meyer et al. 2017), and Sprint 8 (Meyer et al. 2017). The variation of protocols during workouts has greatly made the training session more exciting compared to continuous training (CT) (Driver 2012). The variables that can be manipulated during HIIT are types of workouts (running, cycling, rowing etc.), intensity and duration of high-intensity interval, intensity, duration of recovery interval, number of sets/bouts, and number of repetitions. Intriguingly, the protocol variations have significantly enabled a vast majority of individuals, from a well-trained individual, untrained individual, as well as clinical population to incorporate HIIT as a favorable exercise regime (Driver 2012). For instance, untrained or insufficiently active individual that concern about the high level of exertion may merely make the high-intensity periods slightly less intense with a shorter duration and increase the length of recovery. For people who led hectic lifestyles, HIIT grants them to achieve all the benefits of a longer workout session in a significantly far shorter duration. Studies have showed that HIIT is well known to elicit countless health benefits such as increase cardiorespiratory fitness within as little as two weeks (Martin-Smith et al. 2020) increase immune function (Nieman and Wentz 2019; Gleeson et al. 2012), increase antioxidant status (de Sousa et al. 2017; Ma et al. 2017), and improve bone health (Benedetti et al. 2018; Gómez-Bruton et al. 2017; Archer et al. 2017; Lau et al. 2010; Ooi and Aziz 2017). However, there is less evidence regarding the chronic and acute effects of HIIT on immune system, and there is convincing but mixed data on HIIT response to cardiovascular disease (CVD) risk factors. In addition, the cumulative data on which HIIT protocols offer the most effective methods in the role of improving immune system and inhibiting CVD development are not well explained. It is also uncertain on which protocols, type of exercise movements, duration, and volume constitute optimal training for inducing the desired change in immune function and CVD risk factors. To the best of our knowledge, no previous reviews on the effect of HIIT protocols variation on immune response and CVD risk factors have been conducted. The main aim of this paper is to provide a brief summary of the current literature regarding the HIIT protocols variation through the immune functional perspectives and its role in decreasing the risk of CVD risk factors.

High-Intensity Interval Training Protocols Variation Response …

89

2 Materials and Method 2.1 Study Design The search was conducted according to the preferred reporting items for systematic reviews and meta-analyzes extension for scoping reviews (PRISMA-ScR) guidelines (Tricco et al. 2018).

2.2 Data Sources Related studies were searched electronically using the following databases: PubMed (https://pubmed.ncbi.nlm.nih.gov/), Scopus (http://www.scopus.com), Science Direct (https://www.sciencedirect.com/), ISI Web of Science (http://www. webofscience.com), and Cochrane library (http://www.cochranelibrary.com). Peerreviewed articles published in English language up to May 2022 were used. No attempts were done to contact the authors for additional information. In addition, cross-referencing on related previously published study was performed.

2.3 Search Strategy and Data Extraction The following keywords were used during the search: #hiit and (#immunity or #cvd). Studies were further filter at search engine as article only and in English language. Firstly, the articles were reviewed based on the titles and abstracts to determine whether full texts were required for further analysis. Studies were screened for employing HIIT as intervention and immunity and CVD as outcome measures or stimulus. Only controlled trials and laboratory/experimental studies on humans were included in this review. Each full-text manuscript was selected systematically according to the: (i) study objective/s, (ii) characteristics of the study (study design, participants, gender, age, and sample size), (iii) types and duration of the intervention, (iv) targeted outcome/s, and (v) main findings. Due to the nature of this scoping review, the outcomes extracted from those studies were not combined, reanalyzed, or changed. The initial data screening was performed by one of the authors while the reviewing process of the screened data was performed by all authors. Any disagreements were resolved through discussion among reviewers based on the study selection criteria.

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2.4 Study Selection Criteria After searching the above-mentioned database, the results are exported to the reference manager software: Mendeley Desktop version 1.19.8 to remove duplication. Then, publications are screened for eligibility in a stepwise manner. First, titles and abstracts were scanned to identify human controlled trials and laboratory studies that evaluated the effects of HIIT intervention on immunity and CVD risk factors. The intervention criteria comprised of (i) HIIT with control group and (ii) HIIT with other exercise modes. HIIT was described as any exercised implemented at intensity of 75% and above maximum heart rate (HRmax ) with rest interval. Second, the identified studies were checked to determine if at least one of the target outcomes comprised of immune parameters (e.g., IL-6, s-IgA, Neutrophil, Monocyte, Lymphocytes, IL-1β, IL-6, IL-8, IL-17, TNFα, IL-4, IL-10, IL-13, IL-15, TNF-a) or cardiovascular risk factor parameters (e.g., body mass index, waist to hip ratio, blood pressure, fasting blood glucose, total cholesterol [TC], high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], and triglyceride [TG]). In the final step, the full text of the selected studies was carefully reviewed to determine the final eligible articles. The selected studies were screened using the selection criteria as described. The inclusion criteria were (i) any studies employing HIIT intervention such as body weight, running or cycling protocols; (ii) any articles included immune parameters or CVD risk factor as outcome measure; and (iii) any articles involving men and/or women, athletes, adults with/without known diseases, adolescents, or physically inactive/sedentary individuals. Articles with the following criteria were excluded: (i) non-peer-reviewed articles; (ii) any articles testing on nonhuman participants; (iii) any articles published in languages other than English; (iv) any studies combining HIIT with supplement or/and other exercise modes; (v) studies with no control/other exercise mode group; and (vi) studies with no full-text access.

3 Results 3.1 Article Retrieved A PRISMA-ScR flow diagram showing the stages of articles’ screening and selection is shown in Fig. 1. The initial search from the database identified 167 potential articles and 3 articles was identified through cross-referencing. Briefly, only 16 articles were excluded based on the initial screening of titles and abstracts, leading to selection of 79 articles that were potentially relevant to the current study. Further screening of the full text led to the subsequent removal of 63 other articles, resulting in a total of 16 studies that were eligible for data extraction. Pertinent data extracted from each article are presented in Table 1.

Screening

Identification

High-Intensity Interval Training Protocols Variation Response … Records identified from databases (N = 167) PubMed (n = 20) Scopus (n = 42) Web of Science (n = 39) Science Direct (n = 5) Cochrane Library (n = 61)

Eligibility

Additional records identified through Other sources (n = 0) Cross references (n = 3)

Records screened after duplicate removed (n = 95) Duplicate (n = 75)

Records screened (n = 95)

Included

91

Full-text articles assessed for eligibility (n = 79)

Studies included in qualitative synthesis (n = 16)

Articles removed by title/abstract (n = 16)

Full-text articles excluded with reasons of -Non-related parameters (n = 5) -HIIT with supplement (n = 5) -HIIT combined with strength training (n = 3) -No control group/ other intervention (n = 6) -Full-text not available (n = 41) -HIIT with medication (n = 2) -Only study protocol (n = 1)

Fig. 1 PRISMA-ScR flow diagram for the study selection

3.2 Article Characteristics All 16 articles were published between year 2015 to 2022. Specifically, articles were published in 2016 (n = 1) (Racil et al. 2016), 2017 (n = 3) (Adams et al. 2017; Bartlett et al. 2017; Born et al. 2017), 2018 (n = 2) (Barry et al. 2018; Jamurtas et al. 2018), 2019 (n = 2) (Alonso-Fernández et al. 2019; TaheriChadorneshin et al. 2019), 2020 (n = 1) (Toohey et al. 2020), 2021 (n = 4) (Coletta et al. 2021; Ellyas et al. 2021; Marcotte-Chénard et al. 2021; Ramos et al. 2021), and 2022 (n = 2) (Alonso-Fernández et al. 2022; Meng et al. 2022). There was a total sample of 611 participants across all articles consisting of various population; adolescents (n = 2) (Ellyas et al. 2021; Meng et al. 2022), athletes (n = 1) (Born et al. 2017), healthy (n = 3) (Alonso-Fernández et al. 2019, 2022; Jamurtas et al. 2018), sedentary (n = 1) (Bartlett et al. 2017), diseased: cancer (n = 2) (Adams et al. 2017; Toohey et al. 2020), diabetes (n = 2) (Marcotte-Chénard et al. 2021;

Type Warm up Cool-down

Healthy untrained adolescents

N = 60

16.1 ± 0.4

30/30

IL-6

Population

Sample size

Mean age

Sex M/F

Parameter

2 4–6 90 s of 60–70% HRmax 25–30 min 3 6 weeks

Repetition Rest interval Time per session Frequency Study period

30 s of 80–95% HRmax

N/A

5 min

Intermittent run

N/A

Sets/bouts

Intensity

Mode

Randomized control trial

Study design

Ellyas et al. (2021)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 HIIT protocols and key findings Key findings

(continued)

MICT (n = 30) ↔ plasma IL-6 levels at the first and last six weeks HIIT IL-6 means acute increase in HIIT at the end of the activity

Comparable group

92 N. S. N. Zaid et al.

Type Warm up

Cool-down

Recreational male runner

N = 28

25 ± 4

0/28

s-IgA

Population

Sample size

Mean age

Sex M/F

Parameter

4 1 3 min of ~ 70% of HRmax N/A 3 3 weeks

Repetition Rest interval Time per session Frequency Study period

4 min of 90–95% HRmax

N/A

10 min of 70% HRmax including short bouts (30–45 s) with a higher running intensity

Running

N/A

Sets/bouts

Intensity

Mode

Randomized control trial

Study design

Born et al. (2017)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued)

↑ s-IgA secretion rate was higher with the HIIT on T1, T9 and follow-up

LSD (n = 12)

(continued)

Key findings

Comparable group

High-Intensity Interval Training Protocols Variation Response … 93

Type Warm up Cool-down

Healthy inactive individuals

N = 27

43 ± 11

9/18

Monocyte, WBC, Sets/bouts Lymphocytes, Repetition IL-6, TNFα, IL-10, Rest BF %, BMI interval

Population

Sample size

Mean age

Sex M/F

Parameter

18–25 min 3 10 weeks

Frequency Study period

45–120 s active rest

N/A

N/A

15–60 s OF > 90% HRmax

N/A

5 min of low-intensity cycling

Cycling - cycle ergometer

Supervised

Time per session

Intensity

Mode

Randomized control trial

Study design

Bartlett et al. (2017)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued) Key findings

(continued)

MICT (n = 13) ↓ BF % observed for HIIT ↓ CD14 + /CD16 monocytes % were observed in HIIT ↔ monocytes % for HIIT ↑ monocytes bactericidal function for HIIT ↔ BMI ↔ Total WBC ↔ IL-6 ↔ TNFα Limitation reported; high proportion of women volunteers

Comparable group

94 N. S. N. Zaid et al.

Type

Warm up Cool-down

Sedentary female breast cancer survivors

N = 17

62 ± 8

0/17

s-IgA

Population

Sample size

Mean age

Sex M/F

Parameter

1 4–7 2 min of active recovery 20–30 min 3 12 weeks

Repetition Rest interval Time per session Frequency Study period

30 s of as hard as possible (96–115 rpm)

5 min of ~ 50% maximal power (watts)

5 min of ~ 50% maximal power (watts)

Cycling-cycle ergometer

Supervised

Sets/bouts

Intensity

Mode

Pilot three-arm randomized controlled trial

Study design

Toohey et al. (2020)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued)

↔ salivary IgA concentration before and after HIIT Limitation reported: Saliva collection protocol was based on relying the volunteers to remember the protocol and self-reported timing

CMIT (n = 5), CON (n = 6)

(continued)

Key findings

Comparable group

High-Intensity Interval Training Protocols Variation Response … 95

Sprint interval-cycle ergometer N/A

Inactive Type overweight healthy Chinese female university student Warm up Cool-down

N = 42

21.2 ± 1.4

0/42

Glucose, BMI

Sample size

Mean age

Sex M/F

Parameter

80 1 9s

20 min 3 12 weeks

Repetition Rest interval Time per session Frequency Study period

6 secs sprint (>100 rpm on 1 kg + 0.5 kg of 5% body mass)

N/A

Sets/bouts

Intensity

Supervised

Population

Mode

Randomized control trial

Study design

Sun et al. (2019)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued)

52–61 min

3 min of passive recovery

1

8–10

4 min of 90% VO2 peak (in watt)

Cycling-cycle ergometer

Key findings

(continued)

MICT (n = 14) ↓ BMI ↔ serum glucose level Limitation reported: small sample size

Comparable group

96 N. S. N. Zaid et al.

Cycling-cycle ergometer 3 min

Adults with obesity Type Warm up Cool-down

N = 33

50 ± 7.6

5/28

IL-10, IL-6, TNFα, Sets/bouts leukocytes, Repetition monocytes Rest interval

Sample size

Mean age

Sex M/F

Parameter

12–25 min 5 2 weeks

Frequency Study period

1 min recovery periods at a low intensity

1

4–10

1 min of ~ 90% HRmax

Time per session

Intensity

2 min

Supervised

Population

Mode

Randomized control trial

Study design

Barry et al. (2018)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued) Key findings

(continued)

MICT (n = 17) ↔ IL-10 ↔ IL-6 ↔ TNFα ↔ monocytes count ↔ leukocytes count Limitation reported; short period of intervention, high proportion of female volunteer

Comparable group

High-Intensity Interval Training Protocols Variation Response … 97

Running 10 min

Healthy Type overweight women Warm up Cool-down

N = 28

30.03 ± 3.13

0/28

TNF-a, BMI, Body Sets/bouts fat, WHR, HDL, Repetition LDL, TG, TC, Rest glucose, interval

Sample size

Mean age

Sex M/F

Parameter

N/A 3 8 weeks

Frequency Study period

30 s of walking

2–6

1

30-s with maximum speed of 20 m path

5 min

Time per session

Intensity

N/A

Population

Mode

Randomized control trial

Study design

TaheriChadorneshin et al. (2019)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued)

↓ BMI ↓ BF (%) ↓ WHR ↑HDL ↓ TG, TC, LDL levels ↓TNF-a ↔ glucose Limitation reported: small sample size

CG (n = 14)

(continued)

Key findings

Comparable group

98 N. S. N. Zaid et al.

Type

Warm up Cool-down

Postmenopausal women with overweight or obesity

N = 33

64.4 ± 6.2

0/33

IL-6

Population

Sample size

Mean age

Sex M/F

Parameter

4 1 3 min of 50–70% HRmax 33 min 3 12 weeks

Repetition Rest interval Time per session Frequency Study period

4 min of 90–100% HRmax

5 min at 50–70% HRmax

5 min at 50–70% HRmax

Treadmill walking/running

Supervised

Sets/bouts

Intensity

Mode

Randomized control trial

Study design

Coletta et al. (2021)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued) Key findings

(continued)

MICT (n = 10), ↔ IL-6 UC (n = 11) Limitation reported: inconsistent timing for blood collection in relation to last workout, small sample size

Comparable group

High-Intensity Interval Training Protocols Variation Response … 99

Type Warm up

Cool-down

Adolescent boys with obesity

N = 45

11.2 ± 0.7

36/0

BMI, %BF, WC, Glucose, TG, HDL, LDL

Population

Sample size

Mean age

Sex M/F

Parameter

2 8 15 s at 40 ~ 60% HRmax , 3 min rest between sets 11 min 3 12 weeks

Repetition Rest interval Time per session Frequency Study period

15 s of 80 ~ 90% HRmax

5 min at 55 ~ 60% HRmax

5 min jogging at 55 ~ 60% HRmax + 1 min dynamic stretching + 1 min acceleration running

Running

Supervised

Sets/bouts

Intensity

Mode

Randomized control trial of parallel group

Study design

Meng et al. (2022)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued) Key findings

(continued)

MICT (n = 15), ↓ BMI CON (n = 15) ↓ %BF ↓ LDL ↑ HDL ↔ WC ↓ glucose ↔ TC ↔ TG Limitation reported: small sample size, only boys included

Comparable group

100 N. S. N. Zaid et al.

Cycling-cycle ergometer N/A

Healthy young men Type Warm up Cool-down

N = 12

22.4 ± 0.5

0/28

WBC, lymphocytes, monocytes, granulocytes

Sample size

Mean age

Sex M/F

Parameter

4 1 4 min of recovery against a resistance of 0.375 kg/kg of body mass N/A N/A ACUTE

Repetition Rest interval Time per session Frequency Study period

30 s sprints against a resistance of 0.375 kg/kg of body mass

Sets/bouts

Intensity

N/A

N/A

Population

Mode

Randomized crossover design

Study design

Jamurtas et al. (2018)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued)

↑ WBC following HIIT ↑ Lymphocytes (%) following HIIT immediately post-exercise ↔ Monocytes ↓ Granulocytes (%) following HIIT immediately post-exercise

CET (n = 12)

(continued)

Key findings

Comparable group

High-Intensity Interval Training Protocols Variation Response … 101

Type

Warm up Cool-down

physically inactive older women with type 2 diabetes (T2D)

N = 30

57.1 ± 4

0/30

TC, HDL, LDL, TG

Population

Sample size

Mean age

Sex M/F

Parameter

6 1 2 min at 45% HRR 25 min 3 12 weeks

Repetition Rest interval Time per session Frequency Study period

1 min intervals at 90% HRR

2 min at 40% HRR

3 min (2 min at 55% HRR and 1 min at 75% HRR

Walking

Supervised

Sets/bouts

Intensity

Mode

Randomized parallel group study

Study design

Marcotte-Chénard et al. (2021)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued) Key findings

MICT (n = 16) ↔ TC ↔ HDL ↔ LDL ↔ TG

Comparable group

(continued)

102 N. S. N. Zaid et al.

Type

Warm up Cool-down

Adults diagnosed with metabolic syndrome

N = 99

57.1 ± 4

0/30

TG, HDL, LDL, TC, WC, HC, BF%, BMI, glucose

Population

Sample size

Mean age

Sex M/F

Parameter 3 min at 50–70% HRmax 17 min 3 16 weeks

Rest interval Time per session Frequency Study period

38 min

1

4

1

Repetition

4 min bouts of high-intensity interval training at 85–95% HRmax

3 min at 50–70% HRmax

10 min

Cycle or treadmill ergometer according to participant reference

Semi-supervised

Sets/bouts

Intensity

Mode

Randomized trial

Study design

Ramos et al. (2021)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued) Key findings

MICT (n = 26) ↓ TG ↔ HDL ↔ LDL ↔ TC ↓ WC ↔ HC ↔ BF% ↔ BMI ↓glucose

Comparable group

(continued)

High-Intensity Interval Training Protocols Variation Response … 103

Uphill treadmill walking/running

5 min

Men with a Type confirmed history of testicular cancer Warm up Cool-down

N = 63

43.7 ± 10.8

63/0

TC, HDL, LDL, TG, glucose

Sample size

Mean age

Sex M/F

Parameter

4 1 3 min of 5–10% below the ventilatory threshold 35 min 3 12 weeks

Repetition Rest interval Time per session Frequency Study period

4 min of 75–95% of VO2 peak

Sets/bouts

Intensity

5 min

Supervised

Population

Mode

Prospective 2-armed, phase 2, randomized controlled trial

Study design

Adams et al. (2017)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued) Key findings ↓ TC ↑ HDL ↓ LDL ↔ TG ↔ glucose

Comparable group UC (n = 28)

(continued)

104 N. S. N. Zaid et al.

Type

Warm up Cool-down

Healthy adult

N = 21

35.4 ± 5.6

11/10

BMI, FM (%)

Population

Sample size

Mean age

Sex M/F

Parameter

2–4 8 10 s 8–16 min 2–3 8 weeks

Repetition Rest interval Time per session Frequency Study period

20 s intensive workout

N/A

5 min walk + 10 min joint mobility with dynamic stretching

Tabata body weight functional exercise (squat jump, push up, high skipping, burpees, isometric front plank, multi-jump on bench, mountain climber, lateral sprint

Supervised through video conference

Sets/bouts

Intensity

Mode

Randomized crossover design

Study design

Alonso-Fernández et al. (2022)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued) Key findings ↔ BMI ↓ BF%

Comparable group CG (n = 10)

(continued)

High-Intensity Interval Training Protocols Variation Response … 105

Type Warm up

Cool-down

Healthy obese female adolescent

N = 47

14.2 ± 1.2

0/47

BMI, BF (%), WC

Population

Sample size

Mean age

Sex M/F

Parameter

8–10 1 15 s of 50% MAS 34–38 min 3 12 weeks

Repetition Rest interval Time per session Frequency Study period

15 s of 100% MAS

5 min of jogging at low intensity + 5 min of static stretching exercises

10 min of jogging at 50% MAS + 5 min of dynamic stretching exercises + 5 accelerations on 20 m with 1 min of recovery between

Outdoor running

N/A

Sets/bouts

Intensity

Mode

Randomized control trial

Study design

Racil et al. (2016)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued) Key findings ↓ BMI ↓ BF% ↓WC

Comparable group MIIT (n = 16), control group (n = 14)

(continued)

106 N. S. N. Zaid et al.

Type Warm up

Secondary school students

N = 26

15–16

15/13

BMI, BF (%),

Population

Sample size

Mean age

Sex M/F

Parameter 8 10 s 4–8 min 2 7 weeks

Rest interval Time per session Frequency Study period

Key findings ↓ BF% ↔ BMI

Comparable group Control (n = 13)

MICT Moderate Intensity Continuous Training; HIIT High-Intensity Interval Training; LSD Long-slow Distance Training; CMIT Continuous Moderate Intensity Training; UC Usual Care; CG Control Group; CON Control; MIIT Moderate Intensity Interval Training; CET Continuous Aerobic Exercise; T1 First Day; T9 Last Day; HRmax Maximal Heart Rate; N/A Not Available; BMI Body Mass Index; BF Body Fat; WHR Waist Hip Ratio; WC Waist Circumference; HC Hip Circumference; HDL High-density Lipoprotein; TG Triglycerides; TC Total Cholesterol; LDL Low-density Lipoprotein; WBC White Blood Cell; IL-6 Interleukin 6; IL-10 Interleukin 10; TNFα Tumor Necrosis Factor-Alpha

1–2

Repetition

20 s of maximal effort

N/A

4 min continuous run + 1 min stretch

Tabata functional body weight exercises

Supervised

Sets/bouts

Intensity

Cool-down

Prospective Mode 2-armed randomized control trial

Study design

Alonso-Fernández et al. (2019)

HIIT protocol

Study characteristics

Author/s, Year

Table 1 (continued)

High-Intensity Interval Training Protocols Variation Response … 107

108

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Ramos et al. 2021), and overweight/obese (n = 5) (Barry et al. 2018; Coletta et al. 2021; Racil et al. 2016; Sun et al. 2019; TaheriChadorneshin et al. 2019). Eight studies were randomized controlled trials (Barry et al. 2018; Bartlett et al. 2017; Born et al. 2017; Coletta et al. 2021; Ellyas et al. 2021; Racil et al. 2016; Sun et al. 2019; TaheriChadorneshin et al. 2019). While other studies were prospective twoarm randomized control trial (Adams et al. 2017; Alonso-Fernández et al. 2019), pilot three-arm randomized control trial (Toohey et al. 2020), parallel group randomized control trial (Marcotte-Chénard et al. 2021; Meng et al. 2022), randomized crossover (Alonso-Fernández et al. 2022; Jamurtas et al. 2018), and randomized trial (Ramos et al. 2021). In total, the participants were divided into the intervention and control groups, with sample sizes ranging from n = 12 to n = 99.

3.3 HIIT Intervention Protocols The number of studies that reported on each of the following FITT principles (frequency, intensity, time, type) is as follows: frequency 16/16, intensity 12/16, times 16/16, and type 16/16. Twelve studies prescribed 3 sessions of HIIT per week (Adams et al. 2017; Bartlett et al. 2017; Born et al. 2017; Coletta et al. 2021; Ellyas et al. 2021; Marcotte-Chénard et al. 2021; Meng et al. 2022; Racil et al. 2016; Ramos et al. 2021; Sun et al. 2019; TaheriChadorneshin et al. 2019; Toohey et al. 2020). One study prescribed two sessions per week (Alonso-Fernández et al. 2019), one study prescribed five sessions per week (Barry et al. 2018), one study prescribed two to three sessions per week (Alonso-Fernández et al. 2022) while only one study investigated acute effect of HIIT (Jamurtas et al. 2018). The duration of interventions ranged from 2 weeks to 16 weeks. In the aspect of type of exercise, five studies used running (Barry et al. 2018; Born et al. 2017; Ellyas et al. 2021; Meng et al. 2022; Racil et al. 2016), five studies used cycling or spinning (Barry et al. 2018; Bartlett et al. 2017; Jamurtas et al. 2018; Sun et al. 2019; Toohey et al. 2020), one study used cycling or running (Ramos et al. 2021), two studies used body weight exercise (Alonso-Fernández et al. 2019, 2022), one study used walking (Marcotte-Chénard et al. 2021), and two studies used walking or running (Adams et al. 2017; Coletta et al. 2021). In the aspect of time, the selected studies did not implement the same duration. The shortest duration implemented was 4–8 minutes (Alonso-Fernández et al. 2019), and the longest duration was 52–61 minutes (Sun et al. 2019). Three studies did not report the duration of time per session (Born et al. 2017; Jamurtas et al. 2018; TaheriChadorneshin et al. 2019). Two studies implemented Tabata protocol of 20/10 seconds of work/rest ratio (Alonso-Fernández et al. 2019, 2022), three studies implemented spinning above >90% HRmax (Barry et al. 2018; Bartlett et al. 2017; Sun et al. 2019), four studies implemented running at 80–95% HRmax 19, 20, 27, 30], one study involved cycling at 96–115 rpm (Toohey et al. 2020), one study involved cycling against resistance (Jamurtas et al. 2018), one study involved 30 seconds maximum speed running on 20 m path (TaheriChadorneshin et al. 2019),

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one study implemented outdoor running (Racil et al. 2016), and two studies involved treadmill walking or running at 75% to 95% VO2peak (Adams et al. 2017), 90% HRR (Marcotte-Chénard et al. 2021), and 90–100 HRmax (Coletta et al. 2021). Nine studies were supervised directly by researchers (Adams et al. 2017; AlonsoFernández et al. 2019; Barry et al. 2018; Bartlett et al. 2017; Coletta et al. 2021; Marcotte-Chénard et al. 2021; Meng et al. 2022; Sun et al. 2019; Toohey et al. 2020), one study was semi-supervised (Ramos et al. 2021), one study was supervised through video conference (Alonso-Fernández et al. 2022), while another 5 studies did not mention about supervision (Born et al. 2017; Ellyas et al. 2021; Jamurtas et al. 2018; Racil et al. 2016; TaheriChadorneshin et al. 2019).

3.4 Effect of HIIT on Immune Parameter The effect of HIIT on selected immune parameters (IL-6, TNFα, IL-10, s-IgA, monocyte, WBC, or lymphocytes) was investigated in eight studies. Four studies showed no significant improvement in IL-6 level at post-intervention (Barry et al. 2018; Bartlett et al. 2017; Coletta et al. 2021; Ellyas et al. 2021). However, another study reported a negligible higher mean increase of plasma IL-6 level in HIIT group compared to MICT at the last day of exercise, which was statistically insignificant (Ellyas et al. 2021). One study showed non-significant improvement in IL-10 level at post-intervention (Barry et al. 2018). Similarly, another study reported non-detectable IL-10 on posttest in both HIIT and MICT groups, despite of detectable baseline in HIIT (Bartlett et al. 2017). One study showed statistically significant improvement in s-IgA secretion rate (Born et al. 2017), while another study showed no significant differences of sIgA over time or between groups post-intervention (Toohey et al. 2020). One reported no statistically significant improvement in monocytes post-intervention (Jamurtas et al. 2018). However, a significant change score in CD14 + /CD16 + and TLR4 between HIIT and MICT was reported in this study (Jamurtas et al. 2018). One study reported no statistically significant improvement in total white blood cells postintervention (Bartlett et al. 2017), while another study that measure acute response reported statistically significant improvement in total white blood cell post-exercise (Jamurtas et al. 2018). One study showed statistically significant improvement in lymphocytes (Jamurtas et al. 2018), while another study reported no significant differences lymphocytes over time or between groups post-intervention (Bartlett et al. 2017). One study reported a statistically significant reduction in TNFα from the baseline in HIIT group and a significant difference from control group (TaheriChadorneshin et al. 2019) However, two study reported no significant differences of TNFα over time or between groups post-intervention (Bartlett et al. 2017; Barry et al. 2018).

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3.5 Effect of HIIT on Cardiovascular (CVD) Risk Factor The effect of HIIT on selected cardiovascular risk factors (BF %, BMI, WC, HC, WHR, glucose, HDL, LDL, TG, and TC) was investigated in eleven studies. One study showed no statistically significant reduction in FM % from the baseline in HIIT group and a significant reduction in BF % in MICT group (Bartlett et al. 2017). In contrast, two studies showed a significant reduction in BF % in HIIT group (AlonsoFernández et al. 2019; TaheriChadorneshin et al. 2019). Another study showed a statistically significant reduction in BF % from the baseline in HIIT group, and MICT group with MICT group had a greater reduction (Meng et al. 2022). However, a statistically significant reduction in BF % from the baseline in HIIT group and MIIT group with HIIT group had a slightly greater reduction was reported (Racil et al. 2016). In contrast, a different study reported no statistically significant reduction in BF % from the baseline in all 4HIIT, 1HIIT, and MICT group (Ramos et al. 2021). Another study reported in contrast that both HIIT and control group had a statistically significant changes in BF % from baseline (Alonso-Fernández et al. 2022). However, two studies reported no significant differences of BF % over time or between groups post-intervention (Bartlett et al. 2017; Ramos et al. 2021). Three studies (Meng et al. 2022; Racil et al. 2016; TaheriChadorneshin et al. 2019) showed statistically significant reduction in BMI while another three studies reported no significant differences of BMI over time or between groups post-intervention (Alonso-Fernández et al. 2019, 2022; Ramos et al. 2021). A study reported a statistically significant reduction in BMI from the baseline in HIIT group, and MICT group with HIIT group had a greater reduction (Meng et al. 2022). Different study showed a statistically significant reduction in BMI from the baseline in HIIT, MICT, and SIT group; however, no differences in decrement among group were found (Sun et al. 2019). Meanwhile, a statistically significant reduction was reported in WHR compared to baseline in HIIT group, while control group remains constant (TaheriChadorneshin et al. 2019). Similarly, another study also reported a statistically significant reduction in WC compared to baseline in HIIT group while control and MIIT group remain constant (Racil et al. 2016). In contrast, two studies reported no statistically significant differences of WC and HC in post-test in all group, respectively (Meng et al. 2022; Ramos et al. 2021). A study reported no statistically significant reduction in glucose from the baseline in HIIT group and a significant reduction in glucose in MICT group (Sun et al. 2019). In contrast, another study reported significant reduction in glucose from the baseline in both HIIT and MICT group (Meng et al. 2022). Two studies reported no significant reduction in glucose in all groups (Ramos et al. 2021; TaheriChadorneshin et al. 2019). Another two studies reported a statistically significant improvement in HDL and LDL compared to baseline in HIIT group, while control and MICT group remain constant, respectively (Meng et al. 2022; TaheriChadorneshin et al. 2019). In contrast, three studies reported no statistically significant differences of HDL and LDL in post-test in all group, respectively (Adams et al. 2017; Marcotte-Chénard et al. 2021; Ramos et al. 2021).

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One study reported a statistically significant reduction in TG and TC in HIIT group at post-test, while control and MICT group remain constant, respectively (TaheriChadorneshin et al. 2019). In contrast, four studies reported no statistically significant differences of in TG and TC at post-test in all groups (Adams et al. 2017; Marcotte-Chénard et al. 2021; Meng et al. 2022; Ramos et al. 2021).

4 Discussion Overall, the majority of studies conducted HIIT workout at a frequency of three times per week at the intensity range of 75–95% HRmax in 6-s to 4 min, which led to significant changes in s-IgA secretion rate, monocyte CD14+/CD16 and TLR4, acute total white blood cell and lymphocytes and TNFα. Ideally, the intensity of exercise should be as extremely intense as possible to attain the utmost benefits from HIIT (Driver 2012). However, this will only last for a very short duration as exercising at high intensity for extended period of time is difficult due to the rapid build-up of lactic acid and depletion of creatine phosphate (CP) store (Ferguson et al. 2010). This will avert the prolonged period of high-intensity exercise, at which point a recovery period will be expected. Most of the studies incorporated a rest interval involving light exercise at an easier pace from 9 s to 4 min at intensity of 40 ~ 60% HRmax . Similarly, we found studies that incorporated longer recovery period reported improved outcomes in immune response (Born et al. 2017; Jamurtas et al. 2018). This is suggested that overtraining cause excessive systemic fatigue that will slow down the exercise progression meanwhile the recovery period allows the removal of metabolic waste product like lactic acids and CP store will be replenished, enabling the body to perform high-intensity work again (Ferguson et al. 2010). In most HIIT protocol, the exercise was performed in accordance with new WHO 2020 guidelines on physical activity that address 75–150 min of vigorous intensity physical activity per week (Bull et al. 2020; Ferguson et al. 2010). However, three studies did not report the cumulative HIIT duration per week (Born et al. 2017; Jamurtas et al. 2018; TaheriChadorneshin et al. 2019), one study exceeded the guidelines (Sun et al. 2019), and three studies reported the cumulative HIIT duration below recommendation (Alonso-Fernández et al. 2019, 2022; Meng et al. 2022). Correspondingly, DiNicolantonio et al. (2021) reported heavy exertion of exercise for 60 min or longer may elevate the infection risk as the immune system responds to physical exertion in correlation to the amount of physiological stress and workload (DiNicolantonio et al. 2021). This supports the general consensus that shorts bouts of intense exercise up to 60 min are beneficial in enhancing immunosurveillance defense, whereas this will likely decrease when the duration exceeds 60 min as reported in the study (Bartlett et al. 2017). Comparably, HIIT protocol intervention led to positive changes in immune parameters; s-IgA secretion rate (Born et al. 2017), monocyte CD14+/CD16 and TLR4 (Bartlett et al. 2017), acute WBC and lymphocytes (Jamurtas et al. 2018), and TNFα (TaheriChadorneshin et al. 2019).

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In particular, we found that implementation of HIIT did not significantly improve plasma IL-6 levels (Barry et al. 2018; Bartlett et al. 2017; Coletta et al. 2021; Ellyas et al. 2021). This is supported by the previous study that implemented 8 weeks of HIIT in thirty overweight adolescent boys (Vakilii et al. 2021). However, one study reported an increase trend in IL-6 (Ellyas et al. 2021). This increase suggests that exercise intensity affects the plasma level of IL-6 which increase proportionally with exercise intensity immediately post-exercise (Gleeson et al. 2012). This is supported by the facts that HIIT causes the greatest depletion of muscle glycogen; thus, this increases the production of this anti-inflammatory. However, another study reported a significant increase in IL-6 in high volume HIIT (Cullen et al. 2016). This suggests the manipulation of the HIIT protocol variable: the length of work and rest interval, even though the same mode of exercise can produce different adaptations reactions. A study demonstrated the shortest rest interval compared to the other studies which suggest an increased exertion within 25–30 min (Ellyas et al. 2021). The relatively small increase in plasma level IL-6 appears to be insufficient to induce acute systemic anti-inflammatory effects, thus suggesting a longer duration of exercise (Cullen et al. 2016). We also found that the implementation of HIIT showed non-significant improvement IL-10 post-intervention (Barry et al. 2018). Our study was consistent with other studies conducted that reported no significant differences of serum IL-6 in 10 weeks. HIIT in thirty overweight women and 6 weeks of HIIT in overweight male adolescent, respectively (Alizadeh et al. 2019; Nayebifar et al. 2016). In contrast, another study found that 8 weeks of HIIT in overweight adolescent boys had a significant increase in IL-10 (Vakilii et al. 2021). This discrepancy suggests due to the differences in interventional duration and intensity of HIIT protocols as well as population. The studies addressing the anti-inflammatory response to HIIT in overweight/obese population are scarce that warrants more research should be carried out to understand the mechanisms by which HIIT stimulates an anti-inflammatory response in the overweight/obese population (Alizadeh et al. 2019). The previous study conducted the HIIT intervention in a short duration of two weeks in thirty-three adults with obesity (Barry et al. 2018). Therefore, it is likely that the interventional duration is one of the limiting factors for not inducing anti-inflammatory response in obese cohort (Alizadeh et al. 2019). A longer period of training would possibly allow further physiological adaptation that might show more robust effects. In addition, we found that the implementation of 3 weeks HIIT on recreational male runner showed statistically significant improvement in s-IgA secretion rate (Born et al. 2017). This finding was consistent with the previous study that investigated the acute effect after 20-min HIIT in twenty endurance athletes (Monje et al. 2020). However, the finding is not in line with 12 weeks HIIT on sedentary breast cancer survivor (Toohey et al. 2020). One reason for these inconsistent finding might be the differences in high intensity, training status of the volunteers, and the alteration in salivary flow rate. In response to bouts of HIIT, many studies reported a decrease in s-IgA concentration following exercise that recovers to resting levels within 1 h of exercise completion (Alizadeh et al. 2019).

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We found that HIIT workout had no statistically significant changes in acute monocytes post-intervention (Jamurtas et al. 2018). This finding was similar with a study that conducted 6 weeks of Tabata workout in twelve physically inactive male (Noor et al. 2021). However, another study reported a significant reduction in change score of CD14+/CD16 monocytes phenotype in HIIT group in healthy inactive individual and further reported overtraining, muscle damage, and elevated inflammation is the diminishing factor for monocytes bactericidal capacity (Bartlett et al. 2017). Similarly, a significant reduction in the percentage of non-classical monocytes was reported to restore the balance among the CD16+ monocytes after 8 weeks of HIIT in individuals with obesity (de Matos et al. 2019). Phagocytosis of monocytes increases transiently by acute exercise and is associated with the degree of inflammatory response to exercise. Another study also reported that mean monocyte count increased immediately after the acute HIIT and will return to resting levels three hours post-exercise and completely returned to resting levels six hours post-exercise (Belviranli et al. 2017). We also found that HIIT intervention led to statistically significant improvement in lymphocytes percentage (Jamurtas et al. 2018). In contrast, lymphocyte count normally decreases to the pre-exercise value within as little as 30 min following prolonged and/or high-intensity exercise (Walsh et al. 2011). The decrease in lymphocyte concentration in the post-exercise may be at least due to a result of apoptosis mechanism as Mars and colleagues reported that high volume and high intensity led to post-exercise lymphocyte which may reduce individual immunity (Navalta et al. 2007). Regardless, selected study reported no significant differences post 10 weeks intervention (Bartlett et al. 2017). We also found the present studies reported the benefit of HIIT to improve the outcomes of CVD risk factors. Five studies reported statistically significant reduction in BF % from the baseline in HIIT group (Alonso-Fernández et al. 2019, 2022; Meng et al. 2022; Racil et al. 2016; TaheriChadorneshin et al. 2019). This finding is in line with the previous study that implemented 8 weeks HIIT program in obese volunteers (Ouerghi et al. 2017). This suggests that studies that used longer duration of HIIT protocols and interventions with population possessing higher initial fat mass have resulted in greater fat reduction. In contrast, two studies reported no statistically significant reduction in BF % from the baseline despite on implementing 10–16 weeks of HIIT program (Bartlett et al. 2017; Ramos et al. 2021). These inconsistent findings suggest the metabolic differences in fat depots of individual and gender (Gavin and Bessesen 2020). It is advocated that changes in excess post-exercise oxygen consumption (EPOC) mechanisms may be responsible for the effectiveness of HIIT in the reduction of adiposity as HIIT tends to generate a higher EPOC (Andreato et al. 2019). We also found that WHR was significantly reduced in HIIT group compared to baseline (TaheriChadorneshin et al. 2019). Selected study also reported a statistically significant reduction in WC compared to baseline in HIIT group (Racil et al. 2016). This finding is in line with systematic review and meta-analysis that reported HIIT was effective in decreasing WHR and WC (Andreato et al. 2019). In contrast, two studies reported no statistically significant differences of WC and HC in post-test

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in all group, respectively (Meng et al. 2022; Ramos et al. 2021). Another important factor that contributes to mixed findings in the analysis of possible effects of HIIT on reduction of WHR is that most of the studies did not control the diet of the participants. This certainty is exceptionally crucial because there is evidence suggesting that exercise programs without interventions that involve an energetic deficit are ineffective in reducing the total body fat mass (Andreato et al. 2019). Our findings reported no significant reduction in glucose from the baseline in HIIT (Ramos et al. 2021; Sun et al. 2019; TaheriChadorneshin et al. 2019), and only one study reported glucose changes (Meng et al. 2022). Only two studies reported a statistically significant reduction in LDL in HIIT group (Meng et al. 2022; TaheriChadorneshin et al. 2019), and another two studies reported an elevated HDL after 12 weeks of HIIT (Adams et al. 2017; Meng et al. 2022). Our findings were consistent with the previous literature that reported a notably changes in serum parameters by significantly reducing the glucose level, cholesterol, LDL, and increasing HDL (Nystoriak and Bhatnagar 2018). It is clear that reduced LDL and cholesterol along with increased HDL can reduce the risk of cardiovascular diseases (Nystoriak and Bhatnagar 2018). Only one study reported a statistically significant reduction in TG and TC in HIIT group at post-test (TaheriChadorneshin et al. 2019). This suggest that HIIT lowers triglycerides as well as eliminating very low-density lipoprotein (VLDL) which ultimately leads to decreased TG content of plasma (Nystoriak and Bhatnagar 2018). Some studies did not report a desired changes in lipid profile, and this may be due to the low intervention duration of trainings since metabolic changes require extended interventional time (Marcotte-Chénard et al. 2021; Sun et al. 2019). To our knowledge, this is the first scoping review to assess the effects of HIIT’s protocol variations on immune parameters and CVD risk factors. Findings from this review need to be carefully considered as substantial heterogeneity exists between the selected studies, i.e., different population characteristics (age, BMI, health, and fitness status), different follow-up durations, and variation in study protocols among studies. Nevertheless, this review able to provide valuable information in this focused field of study.

5 Conclusion In conclusion, it is apparent that HIIT program had a positive effect on immune response and cardiovascular risk factors. Currently available evidence also suggests that physiological stress produced during HIIT session did not reduce and compromise immune response. The enrollment of high volume HIIT up to 60 min with longer interventional duration is more promising in modulating the immune function and CVD risk factors. Specifically, HIIT regardless of the training intensity and volume may generate a desired changes in the outcome’s measures. The summary from this review allows HIIT to become prolonged existence trend of the preferred

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type of exercise in future. More randomized control trials that compare HIIT protocols variation with specific population and well-controlled methodologies should be conducted in future.

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Nutritional Status and Its Influence on Body Composition Among Healthy Overweight Men During COVID-19 Lockdown Nursharlina Sharan, Nur Syamsina Ahmad, Nur Dalila Adilah Abdul Raof, and Nurulezah Hasbullah

Abstract Daily lifestyle and diet pattern have changed during COVID-19 lockdown period. This study aims firstly to identify energy intake, energy expenditure, energy balance, and estimated energy requirement among overweight men. Secondly, to determine the association between energy intake, energy expenditure, energy balance, and estimated energy requirement with body composition and lastly, to determine which could be the best predictor to influence body composition in overweight men during COVID-19 lockdown period. Thirty-six (n = 36) overweight physically inactive men aged 25 ± 7 years old with body mass index (BMI) 29 ± 5 kg/m2 were recruited in this cross-sectional study. Physical Activity Readiness Questionnaire (PAR-Q), 24-h diet recall, and body composition were recorded. The energy expenditure was calculated by using revised-Harris Benedict equation formula. The relationship between 24-h diet recall, energy expenditure, energy balance, energy requirement, and body composition among overweight healthy men were determined by using the Stepwise Linear Regression. Overall, body weight and body fat percentage were 82 ± 15 kg and 27 ± 7%, respectively. Their mean daily energy intake was higher (2181 ± 587 kcal/day) compared to energy expenditure which was 1042 ± 198 kcal/day which contributed to positive energy balance (1139 ± 585 kcal/day). Energy expenditure and estimated energy requirement were strongly associated with body composition. Nevertheless, there were no significant association between energy intake and energy balance with body composition. In conclusion, poor lifestyle habit with high energy intake and low energy expenditure were negatively affected during COVID-19 lockdown, which could influence body composition.

N. Sharan · N. S. Ahmad (B) · N. D. A. A. Raof Exercise and Sports Science Programme, School of Health Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian, 16150 Kota Bharu, Malaysia e-mail: [email protected] N. Hasbullah Basic and Medical Sciences Unit, School of Dental Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian, 16150 Kota Bharu, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_10

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Keywords Energy intake · Energy expenditure · Energy balance · Energy requirement · Overweight

1 Introduction Overweight and obesity are the major problems in Asia especially in Malaysia. Based on the Malaysian Clinical Practice Guidelines of Obesity (2004) classifications, the national prevalence of overweight and obesity in Malaysia were 33.4% (95% CI: 32.5, 34.4) and 30.6% (95% CI: 29.5, 31.6), respectively. In comparison, it shows that the prevalence of overweight was higher in male adults aged 50–54 years old and the prevalence of obesity was higher in females. Many factors contributing to these statistics, and one of the causes was the accessibility of the food (Ranjit et al. 2015). Delivery was used for food delivery and online groceries shopping. The modernisation and development of technology have facilitated the continuous decline in energy expenditure required for daily living, leading to an increase in sedentariness (Wiklund 2016). Overweight and obesity are the causative factor in the development of several noncommunicable chronic diseases such as cardiovascular disease, diabetes mellitus, cancer, and musculoskeletal disorder (Afshin et al. 2017). Metabolic syndrome includes high blood sugar and high blood pressure that arise from a condition called insulin resistance. Metabolic syndrome is diagnosed by the emergence of three or more of these conditions, elevated blood pressure, reduced high-density lipoprotein (HDL) levels, raised low density lipoprotein (LDL) levels, triglyceride levels, and fasting blood glucose levels, and larger waist circumference (Arum et al. 2018). In addition, the macronutrient intake among overweight and obese was different compared to individuals with ideal weight. A study conducted by Kim and Song (2019) showed males who are metabolically abnormal with normal body weight, obtained a higher proportion of energy from carbohydrate and lower proportions from fat and protein than other groups (metabolically healthy and normal weight, metabolically healthy but obese, metabolically abnormal and obese). Both high and low macronutrient intakes are associated with body fat levels and obesity which has been observed in previous studies (Park et al. 2018; Mansoor et al. 2016; Hall et al. 2015). Thus, this suggests that the variations in carbohydrate, protein, and fat consumption may affect obesity and increase the risk of cardiovascular disease and mortality rate. Furthermore, the median energy intake of Malaysians recorded in NHMS (2015) was 1466 kcal/day, significantly higher among men than women. Recommendation of the macronutrient intake for total energy contribution is 55% for carbohydrates, 16% for protein, and 29% for fat. Low energy expenditure or being physically inactive could contribute to weight gain. High energy intake with low energy expenditure is associated with positive energy balance. Positive energy balance causes the excess energy to be deposited as body fat and contributes to weight gain (Romieu et al. 2017). In addition, the prevalence of overweight and obesity increases when people do not consider energy

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expenditure in their daily dietary intake. Thus, this eating behaviour will increase the number of noncommunicable chronic diseases in our society. Uncontrolled body weight secondary to excessive fat accumulation may impair overall body health. Body fat percentage generally increases with age 20 to 79 years. The cut-off points for body fat percentage are 24.0% in men and 31.4% in women (Hung et al. 2017). Individuals who are overweight and obese are more likely to exceed body fat percentage cut-off points are more likely the individuals who are in overweight or obese categories. Individuals with high body fat are at high risk of developing noncommunicable diseases such as cardiovascular disease, hypertension, and diabetes. Fat accumulation in arteries will affect blood circulation and narrow the blood vessels, leading to high blood pressure. The normal reading for blood pressure is 120/80 mmHg while a persistent elevation of blood pressure of 140/90 or more is diagnosed as hypertension (MSH 2018). The COVID-19 pandemic causes sudden lifestyles changes. Many people changed their eating habits and adopted different lifestyles because of the lockdown. The worst scenario was when they started working from home, their boredom or stress increased and affected them psychologically and physiologically. Psychological and emotional responses to the COVID-19 outbreak may increase the risk of developing dysfunctional eating behaviours (Wang et al. 2020; Montemurro 2020). Therefore, the aim of this study is threefold. First, to identify energy intake, energy expenditure, energy balance, and estimated energy requirement among overweight men. Second, to determine the association between energy intake, energy expenditure, energy balance, and estimated energy requirement with body composition and lastly to determine which could be the best predictor to influence body composition in overweight men during COVID-19 lockdown.

2 Materials and Methods 2.1 Study Design A cross-sectional study with purposive sampling has been conducted to identify nutritional status related to energy intake, energy expenditure, energy balance, and estimated energy requirement in overweight men during the COVID-19 pandemic. Participants involved in this study were healthy men from the Health Campus Universiti Sains Malaysia. Data collection was conducted in January 2021 to March 2021 during COVID-19 (Conditional Movement Control Order, CMCO).

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2.2 Participants Recruitment and Data Collection Location Thirty-six (n = 36) participants were recruited from Health Campus Universiti Sains Malaysia. The location of data collection for the participants varied since the questionnaires could be answered online through Google form using the link shared through mobile application. The inclusion criteria include participants aged 18 to 40 years old, men with Body Mass Index (BMI) in the range between 25.0 kg/m2 and 30 kg/m2 , healthy and physically inactive. However, participant who had history of upper and lower limb injuries for the past six months, participants who are active (do exercise more than three times per week) or involved in any competition or training and have uncontrolled disease, and habits of consuming any nutritional supplements on regular basic were excluded from this study.

2.3 Diet Assessment and Questionnaire 24-h diet recall Participants were required to fill in 24-h diet recall (Martins et al. 2018) form from Google link which was given through mobile application. The dietary recall method was carried out online since the COVID-19 pandemic started to break the chain of COVID-19 infection. The form consists of a few sections such as the questions regarding food intake for each mealtime (breakfast, lunch, afternoon tea, dinner, and supper), amount of foods and drinks, and calories intakes. The participants were asked to record their mealtime, type of meal, quantity taken (based on measuring tools), methods of cooking and recipes of some of the dishes in the google form. Food measuring tools such as teaspoons, tablespoons, cups, bowls, and glass were used to measure the foods and drinks. The calories intake of overweight participants were calculated by using MyNutriDiari 2 application (Fig. 1) launched by the Ministry of Health Malaysia (MOHE). Figure 2 shows the study design of this study. Physical Activity Readiness Questionnaire (PAR-Q). The PAR-Q was developed as a quick self-screening technique to assess the safety or potential dangers of exercising based on participants medical history, present symptoms, and risk factors. In addition, this questionnaire also is used to access current health status of the participants during the study.

3 Data Collection Body Composition The participants were asked questions about their body weight, height, age, and gender. The information gathered is used to manually calculate the participants’ BMI, body fat percentage, and fat free mass. Participants with BMI 25.0 kg/m2 to 30 kg/m2 were selected. Body weight and height were self-measured

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Fig. 1 MyNutriDiari 2 application launched by MOHE

by the participants. No social contact between the researcher and participants during this study. Participants’ BMI, body fat percentage, and fat free mass were calculated using the following formulas. BMI = (Weight(kg))/(Height(m) × Height(m)) Body Fat Percentage (%) = −44.988 + (0.503 × age) + (10.689 × gender) + (3.172 × BMI) − (0.026 × BMI2) + (0.181 × BMI × gender) − (0.02 × BMI × age) − (0.005 × BMI2 × gender) + (0.00021 × BMI2 × age) (Gomez-Ambrosi et al. 2012). Gender: Male = 0, Female = 1. Fat Free Mass = Weight (kg) × (1 − (Body Fat Percentage/100)) (Van Itallie et al. 1990).

3.1 Prediction of Energy Expenditure from Equation In this study, basal metabolic rate (BMR) was calculated by using a formula called Revised Harris Benedict (1984) equation. As for total daily energy expenditure (TDEE) was measured by multiplying the BMR value by Physical Activity Level (PAL) (Ismail et al. 1998). Physical activity level (PAL) is used to estimate a person’s total energy expenditure. PAL has categorised lifestyle into sedentary (PAL = 1.0 − 1.39), low active (PAL = 1.41.59), active (PAL = 1.6 − 1.89), and very active (PAL = 1.9 − 2.49)

Fig. 2 Illustration of the study design

Physical Activity Readiness Questionnaire (PAR-Q)

24-Hours Diet Recall Breakfast, lunch, afternoon tea, dinner and supper Portion Amount of calories Energy intake

Statistical Analysis

Anthropometry and Body Composition Body weight Height Body Mass Index (BMI) Body Fat Percentage Fat Free Mass

Age: 18 – 40 years old (Physically inactive) Body Mass Index (BMI): 25.0 kg/m2 to 30 kg/m2

Energy Expenditure and Estimated Energy Requirement Revised Harris Benedict Equation: Basal Metabolic Rate (BMR) = 88.362 + (13.397 x weight (kg)) + (4.799 x height (cm)) – (5.677 x age) (Roza & Shizgal, 1984) Energy Expenditure or TDEE = BMR x PAL (Ismail et al., 1998) Estimated Energy Requirement

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(Ohkawara et al. 2011). PAL is based on the most frequent activity performed by most individuals over a period or intensity. Revised Harris Benedict Eq. (1984). Basal Metabolic Rate (BMR) = 88.362 + (13.397 × weight (kg)) + (4.799 × height (cm)) − (5.677 × age) (Roza and Shizgal 1984). Energy Expenditure or TDEE = BMR × PAL (Ismail et al. 1998).

3.2 Energy Balance Equation Energy balance is the result of the same energy in and out in an individual. When the energy intake equals energy expenditure, an individual’s body weight can be maintained. When the energy intake is higher than energy expenditure and the energy balance is positive, an individual can gain weight (Donnelly and Smith, 2005; Romieu et al. 2017).

3.3 Estimated Energy Requirement from Equation The energy requirement is also known as the daily requirement for energy (Gerrior et al. 2006). According to Recommended Nutrient Intakes for Malaysia (2017), the estimated energy requirement principles should be based on energy expenditure, including BMR, PAL, the metabolic cost of food, and growth. Factors that affect energy requirement include age, sex, individual, and population variations (NCCFN 2017). The equation of estimated energy requirement shown below is based on BMI 25.0 kg/m2 and above as reference. Estimated Energy Requirement = 1085.6 − (10.08 × age) + PAL × [(13.7 × weight(kg)] + (416 × height (m)] (NCCFN 2017).

3.4 Statistical Analyses The Statistical Package for Social Science (SPSS) version 27.0 (SPSS, Inc., Chicago, IL) was used for data analysis. The distribution of data for normality was assessed by using the Shapiro–Wilk test. Independent t-test was performed to determine the difference between energy intake and energy requirement. The results were presented as means ± standard deviation unless stated otherwise. The association of energy intake, energy expenditure, energy balance, and estimated energy requirement with body composition were analysed using Pearson correlation analysis to report the significant correlation and significant difference. The prediction of the best factor that contributes to body composition (weight, BMI, body fat percentage, and fat free mass) is either energy intake, energy expenditure, energy balance or estimated

126 Table 1 Participants’ anthropometry and body composition

N. Sharan et al. Parameters Age (years)

Means ± SD 25 ± 7

Body composition Weight (kg)

82 ± 15

Height (cm)

169 ± 5

BMI (kg/m2 )

29 ± 5

Body fat (%)

27 ± 7

Fat free mass (kg)

60 ± 6

Data was expressed as means ± standard deviation (SD), BMI Body Mass Index

energy requirement among overweight men is determined by using the Stepwise Linear Regression. Reporting the standardised β-coefficients, standard error values (SE), and p-values.

4 Results 4.1 Anthropometry and Body Composition of the Participants Thirty-six participants completed this study. All participants were men and healthy with no known chronic diseases, based on their responses from PAR-Q results. Participants were physically inactive and not involved in any physical activity during the lockdown period. They are also not taking any supplements in the past six months. Table 1 shows anthropometry and body composition of healthy men during COVID19 pandemic. Based on the results, participants can be categorised as overweight. Body fat was slightly higher than recommended value (less than 24%). Fat free mass was 60 ± 6 kg.

4.2 Energy Intake, Energy Expenditure, Energy Expenditure, and Estimated Energy Requirement in Overweight Men Figure 3 showed participants energy intake, shows participant’s energy intake (EI), estimated energy requirement (EER), energy balance (EB), and total daily energy expenditure (TDEE). Energy intake (EI) was significantly low (p < 0.01) compared to estimated energy requirement (EER) for overweight men. The results also showed that the participants had positive energy balance during lockdown and low total daily energy expenditure (TDEE) which indicate that the participants were physically inactive.

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127 EI, Energy Intake EER, Estimated Energy Requirement EB, Energy Balance TDEE, Total Daily Energy Expenditure

Fig. 3 Average of energy intake (EI), estimated energy requirement (EER), energy balance (EB), and energy expenditure (TDEE). Data was expressed as mean ± standard deviation (SD), N = 36. ** p < 0.001, significant mean difference between EI and EER

4.3 Association of Body Composition with Estimated Energy Requirement The relationship between body compositions with estimated energy requirement are shown in Table 2. There was a strong positive correlation between body weight (r = 0.94, p < 0.001), body height (r = 0.54, p < 0.001), BMI (r = 0.83, p < 0.001), body fat percentage (r = 0.79, p < 0.001), and fat free mass (r = 0.94, p < 0.001) with estimated energy requirement among healthy men during lockdown period. Table 2 Correlation analysis of the association of body composition with estimated energy requirement

Variables

Correlation (r)

p-value

Weight (kg)

0.94

< 0.001**

Height (cm)

0.54

< 0.001**

BMI (kg/m2 )

0.83

< 0.001**

Body fat (%)

0.79

< 0.001**

Fat free mass (kg)

0.94

< 0.001**

BMI Body Mass Index **, p-value < 0.001

128 Table 3 Correlation analysis of the association of body composition with energy expenditure

N. Sharan et al. Variables

Correlation (r)

p-value

Weight (kg)

0.98

< 0.001**

Height (cm)

0.46

< 0.001**

(kg/m2 )

0.90

< 0.001**

Body fat (%)

0.86

< 0.001**

Fat free mass (kg)

0.92

< 0.001**

BMI

BMI Body Mass Index **, p-value < 0.001

4.4 Association of Body Composition with Energy Expenditure The relationship between body composition and energy expenditure is shown in Table 3. There was a strong positive correlation between body weight (r = 0.98, p < 0.001), body height (r = 0.46, p < 0.001), BMI (r = 0.90, p < 0.001), body fat percentage (r = 0.86, p < 0.001), and fat free mass (r = 0.92, p < 0.001) with energy expenditure among healthy men during lockdown period.

4.5 Association of Body Composition with Energy Intake Table 4 shows the relationship between body composition and energy intake among the participants. There was weak correlation between body weight (r = 0.23, p = 0.179), body height (r = 0.14, p = 0.422), BMI (r = 0.21, p = 0.227), body fat percentage (r = 0.22, p = 0.209), and fat free mass (r = 0.20, p = 0.237) with energy intake. However, there was no significant relationship between the variables and energy intake as the p > 0.05. Table 4 Correlation analysis of the association of body composition with energy intake

Variables

Correlation (r)

p-value

Weight (kg)

0.23

0.179

Height (cm)

0.14

0.422

BMI (kg/m2 )

0.21

0.227

Body fat (%)

0.22

0.209

Fat free mass (kg)

0.20

0.237

BMI Body Mass Index

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Table 5 Correlation analysis of the association of body composition with energy balance Variables

Correlation (r)

p-value

Weight (kg)

−0.10

0.558

Height (cm)

−0.02

0.918

BMI (kg/m2 )

−0.10

0.574

Body fat (%)

−0.08

0.654

Fat free mass (kg)

−0.11

0.526

BMI Body Mass Index

4.6 Association of Body Composition and Energy Balance Table 5 presents the relationship between body compositions with energy balance among the participants. There was negative correlation between body weight (r = −0.10, p = 0.558), body height (r = −0.02, p = 0.918), BMI (r = −0.10, p = 0.574), body fat percentage (r = −0.08, p = 0.654), and fat free mass (r = −0.11, p = 0.526) with energy balance. However, no significant relationship between those components.

4.7 Stepwise Linear Regression Analysis of Selected Nutritional Status with Body Composition Energy expenditure and estimated energy requirement were significant predictors of body weight (Table 6) and body fat percentage (Table 7) which accounted for 97.8% and 99.0%, respectively. However, estimated energy requirement was found to be the only best predictor for fat free mass (Table 8). It accounted for 87.0% of the variation in fat free mass. Additionally adjusted R2 was 0.870. Table 6 Stepwise linear regression analysis models predict the best contribution of body weight Variable

Coefficient

SE

p-value

Constant

138.48

20.007

< 0.001

TDEE (kcal/day)

0.16

0.013

< 0.001

Estimated Energy Requirement (kcal/day)

−0.08

0.013

< 0.001

R2

= 0.979

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Table 7 Stepwise linear regression analysis models predict the best contribution of body fat percentage Variable

Coefficient

SE

p-value

Constant

175.21

5.989

< 0.001

TDEE (kcal/day)

0.15

0.004

< 0.001

Estimated Energy Requirement (kcal/day)

−0.11

0.004

< 0.001

R2

= 0.991

Table 8 Stepwise linear regression analysis models predict the best contribution of fat free mass Variable

Coefficient

SE

p-value

Constant

6.24

4.298

0.156

Estimated Energy Requirement (kcal/day)

0.03

0.002

< 0.001

R2

= 0.874

5 Discussion Energy needs are determined by energy expenditure. Therefore, estimating energy requirements should be based on energy expenditure measurements. Energy intake is the energy content in food from major sources of dietary—carbohydrate, protein, and fat (NCCFN 2017). When energy intake equals energy expenditure, a state of energy balance is said to have been achieved, and stable body weight could be maintained (Donnelly and Smith 2005). In the present study, the estimated energy requirement (EER) was significantly higher than energy intake in overweight physically inactive men. This observation suggested that participants might have consumed less energy intake than the energy requirement during the lockdown period. This energy intake in humans can be influenced by feelings of hunger, satiety, and psychological factors (Montemurro 2020; Wang et al. 2020). Estimated energy requirement and total daily energy expenditure were strongly associate with body composition—weight, height, BMI, body fat percentage, and fat free mass compared to energy intake and energy balance. However, energy intake and energy balance did not significantly correlate with body composition. Stepwise linear regression analysis showed the best predictor influencing body weight and body fat percentage in overweight men during COVID-19 lockdown are energy expenditure and estimated energy requirement. On the other hand, fat free mass was only affected by energy requirement. The present study showed that participants consumed high daily energy intake (2181 ± 587 kcal/day). Even though, their energy intake did not meet the estimated energy requirement for overweight men (2670 ± 210 kcal/day), their intake was still high compared to their energy expenditure. According to Gerrior et al. (2006), the estimated energy requirement was calculated based on an individual’s energy intake, energy expenditure, age, sex, weight, height, and physical activity level (PAL) (Gerrior et al. 2006). Participants in this study were physically inactive and

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had low energy expenditure (1042 ± 198 kcal/day) which resulted in positive energy balance (1139 ± 585 kcal/day). Positive energy balance could lead to weight gain. However, this present study did not have information regarding the macronutrient intake such as carbohydrate, protein and fat, which can contribute to weight gain or high energy intake in overweight men. Therefore, for future research, it is recommended to consider analysing the macronutrient intake to determine the contribution factor of high energy intake in overweight participants and a face-to-face interview about the food intake by following the standard operating procedure COVID-19 during the study. Due to the COVID-19 lockdown, people tend to slow down in their physical activities and change their regular dietary intakes. Besides that, during the lockdown, most people are forced to work from home, self-quarantine and practice social distancing. When people know their energy requirements, it helps them to recognise their daily requirements and maintain their desired body weight. Low energy expenditure can affect the basal metabolic rate in physically inactive men because the estimated energy requirement is low. For physically inactive men with normal BMI, the recommendations of energy requirement are 1920 kcal/day while for active men with normal BMI is 2470 kcal/day (NCCFN 2017). This study also demonstrated a significant relationship between the estimated energy requirement and energy expenditure with body composition. However, no significant association between energy intake and energy balance with body composition was observed. Generally, the estimated energy requirement was the best component that affects body weight, body fat and fat free mass. However, energy expenditure only affects body weight and body fat percentage. It is suggested that to have ideal body weight, normal level of body fat percentage and high fat free mass, men should always consume daily intake based on their energy requirement and be active. Nevertheless, as explained, the environment inevitably encourages poor eating patterns, demotivates regular physical activity, and promotes a sedentary lifestyle during the lockdown. According to Recommended Nutrient Intakes for Malaysia (2017) and Woodruff et al. (2009), the physical activity and body weight are the main determinants for the diversity in energy requirements of adult populations with different lifestyles. It is because the energy needs for growth (energy intake) are no longer an energy-demanding factor in adulthood and basal metabolic rate is relatively constant among population groups of a given age and gender. Energy expenditure in humans is determined by the body size, body composition, environment, and behaviour which is important for body maintenance (Westerterp 2017) while estimated energy requirement determinants are body weight and energy expenditure (Woodruff et al. 2009). Regarding fat free mass, a low fat free mass will influence the estimated energy requirement in overweight individuals as they have low basal metabolism. However, Woodruff et al. (2009) showed no difference in basal metabolic need in overweight and normal weight counterparts after adjusting to fat free mass. Unfortunately, since the study conducted during COVID-19 period, there was a limitation in using the laboratory instrument to analyse body composition. In future study, for more accurate results in the participants’ body composition of the

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participants, the bioimpedance analysis is recommended as the body composition results are more detailed than the manual measurement using the weighing scale. This present study findings could educate the nutritionist and physical trainer groups to prescribe the home-based exercise for overweight population during the lockdown and teach them about proper diet. These practices could encourage the maintenance of healthy lifestyle and improve the quality of life in the overweight population to reduce the rate of obesity and the number of chronic diseases in future.

6 Conclusion In conclusion, during the COVID-19 pandemic, overweight men have poor lifestyle habit, consumed high energy intake and have low energy expenditure which could lead to positive energy balance and contributes to body weight gain as the energy may deposits into high body fat.

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Martins FM, de Paula Souza A, Nunes PRP, Michelin MA, Murta EFC, Resende EAMR, de Oliveira EP, Orsatti FL (2018) High-intensity body weight training is comparable to combined training in changes in muscle mass, physical performance, inflammatory markers and metabolic health in postmenopausal women at high risk for type 2 diabetes mellitus: a randomized controlled clinical trial. Exp Gerontol 107:108–115 Montemurro N (2020) The emotional impact of COVID-19: from medical staff to common people. Brain Behav Immun MSH (Malaysian Society Hypertension) (2018) Clinical practice guidelines—management of hypertension 5th edn. Malaysian Society Hypertension NCCFN (National Coordinating Committee on Food and Nutrition) (2017) Recommended nutrient intakes for Malaysia. A report of the technical working group on nutritional guidelines. Ministry of Health Malaysia, Putrajaya NHMS (National Health and Morbidity Survey) (2015) Non-communicable diseases, risk factors & other health problems. Ministry of Health, Malaysia Ohkawara K, Ishikawa-Takata K, Park J, Tabata I, Tanaka S (2011) How much locomotive activity is needed for an active physical activity level: analysis of total step counts. BMC Research Notes Park KB, Park HA, Kang JH, Kim K, Cho YG, Jang J (2018) Animal and plant protein intake and body mass index and waist circumference in a Korean elderly population. Nutrients 10:577 Ranjit N, Wilkinson AV, Lytle LM, Evans AE, Saxton D, Hoelscher DM (2015) Socioeconomic inequalities in children’s diet: the role of the home food environment. Int J Behav Nutr Phys Act 12(1):S4 Romieu I, Dossus L, Barquera S, Blottière HM, Franks PW, Gunter M, Hwalla N, Hursting SD, Leitzmann M, Margetts B, Nishida C, Potischman N, Seidell J, Stepien M, Wang Y, Westerterp K, Winichagoon P, Wiseman M, Willett WC (2017) Energy balance and obesity: what are the main drivers?. Cancer Causes Control: CCC Roza AM, Shizgal HM (1984) The Harris Benedict equation reevaluated: resting energy requirements and the body cell mass. Am J Clin Nutr 40(1):168–182 Van Itallie TB, Yang MU, Heymsfield SB, Funk RC, Boileau RA (1990) Heightnormalised indices of the body’s fat-free mass and fat mass: potentially useful indicators of nutritional status. Am J Clin Nutr 52:953–959 Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS (2020) Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int J Environ Res Public Health 17:1729 Westerterp KR (2017) Control of energy expenditure. Eur J Clin Nutr 71:340–344 Wiklund P (2016) The role of physical activity and exercise in obesity and weight management: time for critical appraisal. J Sport Health Sci 5(2):151–154 Woodruff SJ, Hanning RM, Barr SI (2009) Energy recommendations for normal weight, overweight and obese children and adolescents: are different equations necessary?. Obes Rev Zainudin S, Daud Z, Mohamad M, Boon ATT, Mohamed WMIW (2011) A summary of the Malaysian clinical practice guidelines on management of obesity 2004. J ASEAN Fed Endocr Soc, 26(2):101–101

Development of an Instrument for Assessing Knowledge, Attitude, and Practices of PE Teachers Towards COVID-19 Pandemic: A Rasch Measurement Approach Voon Mui Yee and Chin Ngien Siong Abstract The COVID-19 pandemic has affected and reshaped all levels of the educational system in terms of the teaching and learning approaches globally. The schools were obliged to take measures to mitigate the spread of COVID-19 in order to ensure the students’ health and psychological well-being in this pandemic uncertainty. Thus, the knowledge, attitudes, and practices of the heads of curriculum and PE teachers play a crucial role in their understanding of accepting the behavioural health change measures towards the pandemic. Thus, this study aimed to develop a CVIS instrument (coronavirus in school) to assess the level of knowledge, attitudes, and practices of heads of curriculum and PE teachers towards COVID-19. The CVIS instrument is a type of knowledge, attitude, and practice survey that utilized the Rasch measurement approach. The study involved item construction, the validation process, and item quality analysis to produce reliable, valid, and good-quality items. The CVIS instrument was utilized to perform a real data collection among heads of curriculum and PE teachers in four divisions in Sarawak. The instrument was selfadministered through Google Form, and the data was analysed by using the Winstep programme. The results manifested that the CVIS instrument is unidimensionality, the items have good fit characteristics of items, and the rating scales are functional, yet there were a few items with DIF issues that purposed to improvise. The CVIS instrument is an instrument that can be used to evaluate the knowledge, attitudes, and practices of teachers towards the COVID-19 pandemic. Keywords COVID-19 · Rasch measurement model · KAP survey

V. M. Yee (B) Department of Science, Institute of Teacher Education Tun Abdul Razak, Samarahan, Sarawak, Malaysia e-mail: [email protected] C. N. Siong Institute of Teacher Education Batu Lintang Campus, Kuching, Sarawak, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_11

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1 Introduction The new virus, coronaviruses, is a member of the Coronaviridae family and has been found in avian hosts as well as in various mammals. Initially, coronaviruses only cause mild disease, thus people did not pay adequate attention to it until the day it became worse and was able to cause fatal “acute respiratory syndrome (SAR-CoV)” (Zheng et al. 2020). The transmission of coronaviruses occurs in animals to humans due to the need to consume animal proteins (Li et al. 2007). Therefore, there were a vast number of people infected in Southern China in 2003 due to the “animal-tohuman and human-to-human” transmission plus a lack of control measures awareness at that time. Two types of animals play a vital role in this pandemic: horseshoe bats and civets (Lau et al. 2020). Horseshoe bats are the reservoir for SARS-CoV-like viruses, with civets able to boost the host and make it easy for transmission. The COVID-19 pandemic has affected and reshaped all levels of the educational system in terms of the teaching and learning approaches globally. Concerns have been raised since those infected cases involving children, especially school students, are increasing drastically compared to the early stages of the pandemic. To date, based on the statistics provided by the Ministry of Health, Malaysia, 82,341 children in Malaysia were infected with COVID-19, which involved 26,851 cases (7–12 years old) and 27,402 (13–17 years old). School educators play a critical role in educating students about infection, prevention, and precautions. Teachers are responsible for ensuring students’ safety and wellbeing in school. School educators have to share exact information, control measures, and scientific facts about COVID-19 with students of different ages to enhance their ability to cope with this pandemic. Thus, the first step in educating students is to ensure school educators acquire sufficient knowledge of COVID-19, present positive attitudes, and behaviour, and practice preventive measures in schools for students to observe and imitate. Teachers are dynamic role models for students who can affect them to be better people (Bashir et al. 2014). The interaction between a teacher and students can influence a student’s attitudes and behaviour (Hughes and Chen 2011). Many studies emphasize the importance of knowledge, attitude, and practice (KAP) in finding the level of knowledge, beliefs, and practised by a particular population (ul Haq et al. 2013), because untrustworthy information and negative attitude may cause a community to panic and stress (Lin et al. 2011). As a result, the KAP survey is critical in determining the awareness of knowledge, attitude, and practice towards COVID-19 among the community (Zhong et al. 2020). More recent evidence shows a review of studies that used the KAP survey to identify the level of knowledge, attitude, and practice among health workers, medical students, and the community in a few countries, such as China, USA, UK, Italy, and Jordan (Puspitasari et al. 2020). This review provided a significant affirmation in proving that knowledge directly influenced attitudes and practices towards COVID-19 (Puspitasari et al. 2020). However, as mentioned in this review, the KAP surveys were not focused on the population of primary school educators.

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Similarly, the other existence of the KAP survey towards COVID-19 developed by other researchers is mainly focused on the public, college students, healthcare workers, and patients as their samples. For instance, the previous KAP surveys researches on different countries towards COVID-19 pandemic such as Egyptian, Northern Nigeria, Malaysia, China, and Mozambique (Abdelhafiz et al. 2020; Habib et al. 2021; Azlan et al. 2020; Feldman et al. 2021; Zhang et al. 2020; Cao et al. 2020; Akalu et al. 2020). Previous researches demonstrated a lack of development of a KAP survey that can be used to assess school educators, especially primary school educators. Therefore, it is important to develop an instrument, specifically the KAP survey that measures individual’s knowledge, attitudes, and practices towards the COVID-19 pandemic, especially in the school community, which mainly involves educators. This instrument ensures that they are qualified to guide and protect students in the school compound. People’s constancy in control measures of COVID-19 was influenced by their knowledge, attitudes, and practices (Zhong et al. 2020). Lessons from the past SARS outbreak in 2003 and the Ebola outbreak in 2013 demonstrated that lack of knowledge about the diseases and insufficient perception could cause panic (Tao 2003) and complicate infectious disease prevention (Fraser et al. 2004; Ajilore et al. 2017). This study aimed to develop and validate an instrument (KAP survey) for primary school educators towards COVID-19. Accordingly, it consists of three primary purposes or aims of the study. The first purpose was to construct and develop instrument items that build up the instrument (KAP survey). The second purpose of the study was to validate the instrument for validity and reliability. The researcher emphasis face and content validity and construct validity. At the same time, the researcher highlighted item reliability and person reliability. The third purpose of this study was to evaluate and analyse all the items instruments to fulfil the requirements or assumptions of the Rasch measurement model to develop a good instrument, which are item fit, item dimensionality, rating scale analysis, item reliability, item difficulty, item separation, and differential item functioning (DIF). The Rasch analysis model will be used to analyse the instrument items to ensure all the assumptions of the Rasch model have been fulfilled. For instance, (1) item fit (0.4 < MNSQ < 1.5); (2) items well-distributed along the continuum in the Wright Map; (3) item dimensionality (raw variance explained by measures-minimum 40%, unexplained variance in the first contrast-below 15%); (4) rating scale analysis (1.4 < x < 5.0); (5) item reliability (minimum 0.60); (6) differential item functioning (DIF) of items must less than 0.05. Besides that, the Rasch measurement model was also utilized to measure person data in terms of person reliability, person separation, person ability level, and person fit statistics. Rasch analysis is a psychometric method designed to improve the accuracy and consistency of researchers’ instrumentation, and Rasch analysis is able to avoid all the mathematical errors that commonly occur in a test analysis (Boone 2016). Many science education researchers have used Rasch analysis methods (Reeves and Marbach-Ad 2016).

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2 Methods 2.1 Instrument Development and Validation Processes This research utilized the CVIS instrument, which the researcher designed. The instrument aimed to assess primary school educators’ knowledge, attitudes, and practices towards the COVID-19 pandemic. The instrument consists of four main sections: (1) the demographic information of the respondent; (2) the knowledge section; (3) the attitudes section; and (4) the practices section. The total items in this instrument are 31 items with 4 rating scales (“strongly disagree”, “disagree”, “agree”, and “strongly agree”). The research instrument construction for this research was by utilizing the construct modelling approach, specifically the “four building blocks”. The CVIS instrument was constructed through these four building blocks: (1) the construct map, (2) the item design, (3) the outcome space, and (4) the measurement model. There were a total of 31 items, and all the items can be categorized into three main sections: the knowledge section, the attitude section, and the practices section. Each section consists of a few groups of items with different difficulty levels. In detail, every item consists of an item’s statement and four rating scales, which are: “strongly disagree”, “disagree”, “agree”, and “strongly agree”. Respondents were required to choose only one rating scale among the four rating scales that best matches their responses. The instrument utilized the concept of the KAP survey to assess primary school educators’ knowledge, attitudes, and practices towards COVID-19. The KAP survey is able to gather details of what is known, believed and done by a particular population (ul Haq et al. 2013). Information about individuals’ knowledge, attitudes, and practices is very important because unsure information and negative attitudes towards the COVID-19 pandemic may cause tension and panic (Yang et al. 2020). Besides that, knowledge directly impacts attitudes; thus, increasing the knowledge of the community towards COVID-19 is able to have a positive effect on individuals’ attitudes and their practices towards COVID-19 (Zhong et al. 2020). Therefore, all the items of the CVIS instrument are designed based on credible information from the World Health Organization (WHO), the Centre for Disease Control and Prevention (CDC), the Ministry of Health (MOH), the Ministry of Education (MOE), and the Standard Operating Procedures (SOPs) implemented by the government authorities. The CVIS instrument items are divided into 9 essential themes, which are preventive measures, physical distancing, face mask, hand hygiene, symptoms of the COVID-19, the transmission of the COVID-19, general knowledge of the COVID19, standard operating procedures (SOPs), and misconceptions of the COVID-19. The final product of all the validation processes, which involved expert judgement and three rounds of pilot tests, produced the CVIS instrument.

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2.2 The Rasch Measurement Model The item response theory and the Rasch model were utilized in this research. The Rasch measurement model is the chosen measurement model rather than classical test theory or other mathematical models due to its specific advantages. The Rasch measurement model enables interchangeability between item and respondent due to both having the same interval scale (Sumintono and Widhiarso 2015). The logit equalinterval scale is used to connect the relationship between the test-taker’s ability and the severity level of the item (Sumintono 2017). These properties of Rasch directly allow researchers to use the difficulty level of an item to represent or figure out the actual ability level of the respondent. Moreover, the Rasch measurement model fulfils all the five measurement principles of human sciences (Mok and Wright 2004), which allowed researchers to obtain more precise and meaningful inferences from the data collected (Sumintono 2017). The Rasch measurement model can detect any outliers or misfit data that may occur in the research. The Rasch model software called Winsteps is used to detect outliers and misfit data through these three psychometric attributes: (1) outfit mean square value in between 0.5 and 1.5, (2) Z-standard outfit value in between −2.0 and + 2.0, and (3) value of point measure correlation value in between 0.4 and 0.85 (Sumintono 2017). Any items not in the range of these three psychometric attributes are considered misfit items. The process of reconsidering or re-testing has to be performed for misfit items before deleting them. Moreover, the Rasch measurement model can detect any occurrences of item bias, which is important for this research as it involves respondents with different demographic backgrounds. The issue of bias can occur when items in the research instrument benefit a specific group of respondents. Items with the problem of bias will have a differential item functioning (DIF), and this psychometric can be detected using the Rasch model tools and the Winstep programme. An item can be categorized as a biased item when the value of its DIF-probability is more than 5% (0.05) (Sumintono 2017). In conclusion, the Winstep programme will be utilized to analyse the trait interest in this research. The psychometric properties of the CVIS instrument will be proven through statistical analysis and empirical evidence of item quality. A set of good quality items are items with different item difficulty, high validity, and high reliability.

2.3 Expert Judgement (Face and Content Validity) The CVIS instrument undergoes a validation process to prove the instrument’s face and content validity. The validation process involved several expert judges in assessing all the items in the instrument. Rater-mediated assessment involves a judgemental process that consists of raters or experts to moderate the opportunities and inferences of the assessment system (Engelhard and Wind 2017). The expert judgement process can also be used to confirm an instrument’s accuracy and rating

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quality. A group of expert judges with different fields related to the research topic was assigned to make a judgement by rating each item in the instrument through an expert judgement form. Assessment for rater accuracy needs a “comparison of an individual rater’s rating across performance dimensions and/or ratees with corresponding evaluations provided by expert raters (i.e. ‘True-score’) (Woehr and Huffcutt 1994). With these measures, the closer the raters’ ratings are to the ‘true scores’, the more accurate they are believed to be” (p. 192). Ratings from raters or experts are used to indicate the true or expected scores of the items where the ratings are acquired from expert raters who are chosen according to their expertise with the assessment context, background, experience, training, or qualification (Engelhard 1996; Johnson et al. 2009; Wind and Engelhard 2013). Therefore, researchers must assess the quality of judgements gathered from raters when involving raters in an assessment because the rating of experts affects the validity of the assessment (Engelhard and Wind 2018). Detecting rater effects and measuring rater fit statistics is essential in evaluating and improving instruments (Barkaoui 2013). Rater fit statistics indicate the degree to which a rater is internally self-consistent across criteria and tasks. A misfit rater indicates that the rater exhibits more variation in their rating than expected and is not consistent across tasks. Ratings of misfit raters tend to be “noisy” and have to be “muted” or deleted because they are being unusually consistent (McNamara 1996; Myford and Wolfe 2000, 2004). The many-facet Rasch measurement is an extension of the basic Rasch model by including more aspects (facets), for instance, raters and tasks (Myford et al. 2004; Eckes 2014). This measurement model is used to demonstrate how to measure raters’ severity and leniency, and determine rater consistency (Myford et al. 2004). Two essential dimensions are emphasized in this research: the severity of raters and raters’ internal consistency. The raters are the expert judges who contributed to this research. Measure logit was used to determine the severity of experts in this research. The higher the logit value of the measure, the more severe the expert judges; the lower the logit value of the measure, the more lenient the expert is (Tavakol and Pinner 2019).

2.4 Validity of the CVIS Instrument A unidimensionality instrument has a minimum of 40% of “raw variance explained by measures” and is better at 60%, and the “unexplained variance in the first contrast” is below 15% (Sahin et al. 2016). The “raw variance explained by measures” for this instrument is 55.2%, which is more than 40% and approximately matches the expected model, which is 54.8%. (Aziz et al. 2013) The expected percentage of raw variance is explained by measures closer to the observed percentage. Besides that, the “unexplained variance in first contrast” is 7.5%, which is below 15%. The minimum ratio of raw variance explained by measures and unexplained variance in the first contrast must be at least 3:1 (Linarce 2015; Conrad et al. 2011). The raw variance explained by measures is 55.2% and the unexplained variance in the first contrast is

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7.5, so the ratio is 7.3:1, larger than the minimum ratio of 3:1. Thus, the instrument items managed to fulfil both the criteria for unidimensionality and construct validity. On the other hand, the eigenvalue for raw variance explained by measures for 31 items is 31.0; the eigenvalue for unexplained variance in first contrast is 5.1; and it was more than the acceptable range where it should be between 1.4 and 3.0 (Embretson and Reise 2000). Thus, two items that probably measure another dimension in the instrument, and these two items were proposed to be deleted. The standard residual correlation of the study where all the values of correlation were less than 0.70 and in the acceptable range (Sahin et al. 2016; Maskor and Baharudin 2019). This weak correlation indicates that there is no dependency between items, and the assumption of the Rasch model for local independence and unidimensionality was not violated.

2.5 Reliability of the CVIS Instrument The good item reliability and person reliability are between 0.80 and 0.90, and the ideal reliability is more than 0.94 (Linacre 2009). The item reliability for the 31 measured items was 1.00, which was an ideal index of reliability. The person reliability of all the 1336 respondents was 0.82, which is considered good person reliability. The acceptable item separation is at least 3, able to distinguish 3 groups of difficulty levels of items (Sahin et al. 2016). The item separation index of the study is 34.34, which means items in the instrument can be grouped into 34 different difficulty levels. The acceptable person separation is at least 2 (Sahin et al. 2016). The person separation index of this study is 2.11 (minimum 2). This shows that the instrument can differentiate respondents into two groups of different ability levels. The value of item strata is 45.6 and is considered as 45 different groups of difficulty levels of items. Besides, the person strata index is 3.15, indicating that the instrument items that are able to distinguish respondents into three different ability levels. 82% of the time, the CVIS instrument differentiates respondents into 3 strata (3.15) according to their ability levels. The CVIS instrument has very high consistency (100%), which means the item difficulty levels (45 levels) are consistent and repeatable with a different sample of respondents. Apart from this, the value of Alpha Cronbach was also used to determine the reliability of the interaction between items and respondents. The value of the Alpha Cronbach is 0.80, and it indicates the instrument has good reliability (Fisher 2007). As all the analysis result highlights, it is proven that the CVIS instrument has high reliability and consistency compared to the value of model errors (item: 0.05; person: 0.31).

2.6 Item Difficulty Levels The item difficulty levels spread from the easiest item with −2.52 logit to the most difficult item with 2.65 logit, indicating that the CVIS instrument items were spread

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along a continuum of 5.17 logit. There were 5 difficulty levels which consist of very difficult to endorse/agree items with logit value (> + 2.0), difficult to endorse/agree items with logit values (in between + 0.5 to + 2.0), moderate items (−0.5 to + 0.5), easy to endorse/agree items (−2.0 to −0.5), and very easy to endorse/agree items (< −2.0). To repeat, the 31 items of the CVIS instrument was made up of 7 very difficult items (22.58%), 5 difficult items (16.12%), 6 moderate items (19.35%), 9 easy items (29.03%), and 4 very easy items (12.90%). It was found that the item most difficult to endorse/agree is item A1 with 2.65 logit; the easiest to endorse/agree the item is item K14 with −2.52 logit.

2.7 Item Fit There were three psychometrics features used to identify the suitability of item: outfit mean square (0.5 < Outfit MNSQ < 1.5); Z-standard outfit value (−2.0 < ZSTD < + 2.0); point measure correlation value (0.4 < Pt Measure Corr < 0.85) (Sumintono, B.: Rasch 2017). The value of point measure correlation is acceptable as long as it is positive (Sumintono 2015). All 31 items fulfilled the item fit statistics for OUTFIT MNSQ and point measure correlation. The range of OUTFIT MNSQ for all 31 items is 0.68 to 1.40, in the acceptable range (0.5 < Outfit MNSQ < 1.5), and the range of point measure correlation is within the acceptable range which is from 0.37 to 0.45 (all positive values). The analysis indicated no “outliers” or “misfit” items in the instrument.

2.8 Rating Scales Analysis The acceptable difference between the scales is in the range of 1.4 < s < 5.0 (Hambleton et al. 1991). The quality of the rating scale was utilized in this study to identify whether the categories meet the model’s assumption. The observed count, which is the rating scale chosen by the respondents in this study, is: (rating scale 1 (“strongly disagree” = 8024); 2 (“disagree” = 13,204), 3 (“agree” = 17,233); and 4 (“strongly agree” = 2955)). Besides that, the observed average is used to show the response pattern, and if the values are increasing from negative to positive, it shows the normal pattern. This study’s observed average shows a normal response pattern with a negative value increasing to a positive value (−2.65, −1.06, 0.60, 1.34). In Rasch analysis of the rating scale, the difference between the scale should be between 1.4 and 5.0 (1.4 < s < 5.0) (Sahin et al. 2016). The differences between the scales (1 and 2 = 2.3, 2 and 3 = 1.83, 3 and 4 = 3.45) are within the range of 1.4 < s < 5.0, indicating that the 4-rating scale utilized in this study is functional and fits the Rasch model adequately well.

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3 Conclusion In conclusion, the researcher managed to construct and develop high validity and reliability instrument items based on the proven description above. The CVIS instrument can divide the respondents into two distinct ability groups. In addition, the instrument consists of 31 fit items that fulfil all the main assumptions of the Rasch measurement model. In general, the findings and evidence from the study indicated that all the instrument items were fit based on the acceptable range of outfit mean-square and point correlation measure; all the 31 instrument items measured the same dimension (unidimensionality); rating scales utilized in the instrument were functioning well; only 6 items had slight item bias issues; and the Wright Map which demonstrated that the instrument items corresponded to respondents’ ability levels.

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Eckes T (2014) Reference supplement to the manual for relating language examinations to the Common European Framework of Reference for Languages: learning. Teaching, Assessment, Section H: Many-Facet Rasch Measurement. http://www.coe.int/t/dg4/linguistic/manuel1_e n.asp Embretson SE, Reise SP (2000) Item response theory for psychologists. Mahwah, New Jersey, Lawrence Erlbaum Associates Engelhard G Jr (1996) Evaluating rater accuracy in performance assessments. J Educ Measure 33(1):56–70 Engelhard Jr G, Wind S (2017) Invariant measurement with raters and rating scales: Rasch models for rater-mediated assessments. Routledge Engelhard G, Wind SA (2018) Invariant measurement with raters and rating scales: Rasch models for rater-mediated assessments. Routledge Feldman M, Lacey Krylova V, Farrow P, Donovan L, Zandamela E, Rebelo J, Rodrigues M, Bulo A, Ferraz C, Rodrigues H, Roca-Feltrer A, Baker K (2021) Community health worker knowledge, attitudes and practices towards COVID-19: learnings from an online cross-sectional survey using a digital health platform, UpSCALE, in Mozambique. PloS ONE 16(2):e0244924. https://doi. org/10.1371/journal.pone.0244924 Fisher Jr WP (2007) Rasch measurement: transactions of the Rasch Measurement SIG American Educational Research Association Fraser C, Riley S, Anderson RM, Ferguson NM (2004) Factors that make an infectious disease outbreak controllable. Proc Natl Acad Sci 101(16):6146–6151 Habib MA, Dayyab FM, Iliyasu G, Habib AG (2021) Knowledge, attitude and practice survey of COVID-19 pandemic in Northern Nigeria. PLoS ONE 16(1):e0245176. https://doi.org/10.1371/ journal.pone.0245176 Hambleton RK, Shavelson RJ, Webb NM, Swaminathan H, Rogers HJ (1991) Fundamentals of item response theory, Vol 2. Sage Hasmy A (2014) Compare unidimensional and multidimensional Rasch model for test with multidimensional construct and items local dependence. J Educ Learn 8(3):187–194 Hughes JN, Chen Q (2011) Reciprocal effects of student–teacher and student–peer relatedness: effects on academic self-efficacy. J Appl Dev Psychol 32(5):278–287 Johnson RL, Penny JA, Gordon B (2009) Assesing performance assessment Lau SKP, Luk HKH, Wong ACP, Li KSM, Zhu L, He Z, Fung J (2020) Possible bat origin of severe acute respiratory syndrome Coronavirus 2. Emerg Infect Dis 26(7):1542–1547. https://doi.org/ 10.3201/eid2607.200092 Li P, Yin YL, Li D, Kim SW, Wu G (2007) Amino acids and immune function. Brit J Nutr 98(2):237– 252. https://doi.org/10.1017/S000711450769936X Lin Y, Huang L, Nie S, Liu Z, Yu H, Yan W, Xu Y (2011) Knowledge, attitudes and practices (KAP) related to the pandemic (H1N1) 2009 among Chinese general population: a telephone survey. BMC Infect Dis 11(1):1–9 Linacre JM (2009) Winsteps (version 3.68. 0) [Computer software]. Chicago, Winsteps.Com Linarce JM (2015) Winsteps Rasch measurement computer program user’s guide. Beaverton, OR Maskor ZM, Baharudin H (2019) Assessing psychometric properties of Malaysian secondary school students’ Arabic vocabulary knowledge inventory. Glob J Al-Thaqafah 147–159 McNamara T (1996) Measuring second language performance. Longman, London Mok M, Wright B (2004) Overview of Rasch model families. In: Introduction to Rasch measurement: theory, models and applications. Minnesota, Jam Press, pp 1–24 Myford CM, Wolfe EW (2004) Detecting and measuring rater effects using many-facet Rasch measurement: Part I. In: Jr Smith EV, Smith RM (eds) Introduction to Rasch measurement: theory, models and applications. Maple Grove, Minnesota: JAM Press, pp 460–517 Myford CM, Wolfe EW (2000) Monitoring sources of variability within the test of spoken english assessment system (TOEFL research report, N 65). Princeton, Educational Testing Service

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Myford CM, Wolfe EW (2004) Detecting and measuring rater effects using many-facet Rasch measurement: Part II. In: Smith EV, Smith RM (eds) Introduction to Rasch measurement: theory, models and applications. JAM Press, Maple Grove, Minnesota, pp 518–574 Okoro J, Ekeroku A, Nweze B, Odionye T, Nkire J, Onuoha M, Ezeonwuka C, Owoh J (2022) Attitude and preventive practices towards COVID-19 disease and the impact of awareness training on knowledge of the disease among correctional officers. Emerald Open Res 2:51 Puspitasari IM, Yusuf L, Sinuraya RK, Abdulah R, Koyama H (2020) Knowledge, attitude, and practice during the COVID-19 pandemic: a review. J Multidiscip Healthc 13:727–733. https:// doi.org/10.2147/JMDH.S265527 Reeves TD, Marbach-Ad G (2016) Contemporary test validity in theory and practice: a primer for discipline-based education researchers. CBE Life Sci Educ 15:1–9 Sahin MG, Teker GT, Güler N (2016) An analysis of peer assessment through many facet Rasch model. J Educ Pract 7(32):172–181 Sumintono B (2015) Science education in Malaysia: challenges in the 21st century. Int Seminar Sci Educ 1–10 Sumintono B, Widhiarso W (2015) Aplikasi pemodelan Rasch pada assessment pendidikan. Trim Komunikata Publishing House, Cimahi Sumintono B (2017) Rasch model measurement as tools in assessment for learning. Int Conf Educ Innov Tao N (2003) An analysis on reasons of SARS-induced psychological panic among students. J Anhui Inst Educ 21:78–79 Tavakol M, Pinner G (2019) Using the Many-Facet Rasch Model to analyse and evaluate the quality of objective structured clinical examination: a non-experimental cross-sectional design. BMJ Open 9(9):e029208 ul Haq N, Hassali MA, Shafie AA, Saleem F, Farooqui M, Haseeb A, Aljadhey H (2013) A crosssectional assessment of knowledge, attitude and practice among Hepatitis-B pa- tients in Quetta, Pakistan. BMC Publ Health 6(13):1–9 Wind SA, Engelhard G (2013) How invariant and accurate are domain ratings in writing assessment. Assess Writ 18(4):278–299 Woehr DJ, Huffcutt AI (1994) Rater training for performance appraisal: a quantitative review. J Occup Organ Psychol 67:189–205 Yang Y, Li W, Zhang Q, Zhang L, Cheung T, Xiang YT (2020) Mental health services for older adults in China during the COVID-19 outbreak. Lancet Psychiatry 7(4):e19 Zhang M, Zhou M, Tang F, Wang Y, Nie H, Zhang L, You G (2020) Knowledge, atti- tude, and practice regarding COVID-19 among healthcare workers in Henan, China. J Hosp Infect 105(2):183–187. https://doi.org/10.1016/j.jhin.2020.04.012 Zheng YY, Ma YT, Zhang JY, Xie X (2020) COVID-19 and the cardiovascular system. Nat Rev Cardiol 17(5):259–260 Zhong BL, Luo W, Li HM, Zhang QQ, Liu XG, Li WT, Li Y (2020) Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: a quick online cross-sectional survey. Int J Biol Sci 16(10):1745–1752. https://doi. org/10.7150/ijbs.45221

Enhancing Sustainable Tourism in Kundasang Through Hiking Mohamad Nizam Bin Nazarudin, Muhammad Azim Bin Abdul Rahim, and Norlaila Azura Binti Kosni

Abstract People who hike are more likely to be physically active and spend time in nature, which is a cost-effective strategy. Physical movement, exposure to natural elements, stress reduction, and improved mental and emotional well-being are just some of the health advantages that may be reaped by spending time in the great outdoors. Sabah was a popular hiking destination before the COVID-19 outbreak shut down all tourism activity. Hiking paths can be used to promote sustainable tourism. Hiking has grown in popularity as a means of discovering a new place, and it contributes to the long-term well-being of the area in question. The purpose of this research is to discover and examine the demographic features, the service quality and perceived value of visitors who hiked in Kundasang, Sabah, while on holiday. Questionnaire was designed and consist of SERVQUAL (Akbaba 2006) and SERV-PERVAL (Petrick 2004) for this study. This research was conducted with 232 participants on 12 hiking trails near Kundasang, Sabah. Inferential statistical methods were used to examine the data. This study’s finds relationship among service quality, perceived value, satisfaction, and revisit intention in hiking industry. Understanding the demographics and perceived worth of hikers, as well as refining the marketing tactics for both the local and international markets through sustainable tourism, is a benefit of these findings. Keywords Hiking · Sustainable tourism · Service quality perceived value

M. N. B. Nazarudin (B) Universiti Kebangsaan Malaysia, Selangor, Malaysia e-mail: [email protected] M. A. B. A. Rahim Terengganu Football Club, Kuala Nerus, Malaysia N. A. B. Kosni Universiti Teknologi MARA, Pahang, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_12

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1 Introduction Sustainable tourism is a type of travel that takes into account the environmental, social, and economic effects of tourism and makes changes to reduce these effects as much as possible. It takes into account not only the needs of travellers, but also the needs of host communities, local businesses, and nature. The main goal of sustainable tourism is to reduce the effects of tourism on local communities and the environment. This means making the best use of resources so they aren’t overused, helping to protect the natural world, and making a conscious effort to respect and preserve local traditions and heritage. One of the most important goals of sustainable tourism is to make travel more possible in the long run. This is done through education and changes in behaviour. Sustainable tourism also tries to help local economies and communities, so it is more of a “give and take” relationship. The idea of sustainable tourism is very important because, while travel can help an area’s economy and give people jobs, it can also have negative effects, such as overusing resources, displacing wildlife, and hurting local culture, as well as contributing to greenhouse gas emissions. As tourism is expected to keep growing in the coming years, the way people travel now won’t be able to keep up. This is because the way people travel now hurts the environment, local communities, and the earth’s natural resources too much. Because of this, sustainable travel is important for the tourism industry as a whole in the long run. By making sustainable tourism a top priority, governments, travel companies, airlines, hotels, restaurants, and tourists can all help make sure that tourism will still be possible in future. Tourism can be a force for good in the world if steps are taken to help local people and lessen the damage it causes. This could mean using more environmentally friendly ways to get around, staying in places that are better for the environment, eating food that is grown locally and in an ethical way, and avoiding harmful activities. Sustainable tourism can include travel for business, pleasure, or events, but it can also include travel to see friends and family. Sustainable tourism is a big term that covers a lot of different types of tourism, like ecotourism, community tourism, rural/ethnic tourism, and soft tourism. Recreational hiking in ecotourism or nature-based sites is linked to a number of different health effects on an individual level. One of the most popular ecotourism activities in Malaysia that gets people out into nature and has health and wellness benefits are hiking (Nordin and Jamal 2021). Before COVID-19, the tourism industry was one of the fastest-growing parts of the economy. Now, it is a key driver of social and economic progress all over the world (Nasir et al. 2020). Mountain hiking is becoming more popular in Malaysia because more people are becoming aware of how to live a healthy life, living standards are getting better for everyone, and tourism concepts, health, and wellness are changing at ecotourism sites in the natural setting with adventure activities like hiking (Hairom 2020). Tourists are more interested because people are thinking more about using natural environments for physical activity and recreation to improve health and well-being. Because hiking is a physical activity in natural settings that is good for health and well-being, it has caught the attention of business people and researchers (Lee et al. 2017).

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Hiking has been called one of the biggest parts of nature-based tourism for a long time (Nordin and Jamal 2021), and more and more people are hiking in different places (D’Antonio et al. 2012; Mason et al. 2013). Hiking is walking for a long distance in nature, often over rocks and tree roots. In mountain areas and protected areas, hiking is usually the most popular form of recreation (Fredman and Tyrväinen 2010). It can also bring in a lot of money for the locals through tourism (Wöran and Arnberger 2012). In recent years, a number of rural destinations have put in a lot of work to make hiking easier, taking advantage of tourists’ growing desire for natural experiences (Breejen 2007) and activities that are good for their health and well-being (Smith and Puczko 2014). Even though research found that experience quality is important to tourists (Prebensen et al. 2015) and hiking can improve both mental and physical health and well-being (Bowler et al. 2010), not much research has been done on the many different aspects of hiking from the customers’ point of view. Social, environmental, and management factors have a lot to do with hiking, and it changes over time (Kay and Moxham 1996). Hiking is a great example of a customer producing or co-creating an experience by taking part in it both physically and mentally (Prebensen et al. 2012). Hiking is a good topic for research because it is related to tourism, recreation, and leisure, all of which are often thought of as separate fields (Breejen 2007).

2 Method 2.1 Survey Instrument The questionnaire was designed and divided into three parts. First part is related to service quality dimensions. SERVQUAL (Akbaba 2006) was adopted with some modification in text and questions. All 30 items are included in first part to measure service quality dimensions (Parasuraman et al. 1985). These dimensions are tangibles, reliability, responsiveness, assurance, and empathy. All items were on 7-point Likert scale ranging from strongly agree “1” from strongly disagree “7”. Second part is related with perceived value measurement. SERV-PERVAL (Petrick 2004) with modification in writing and items were used to measure perceived value. SERVPERVAL has five sub-dimensions which are “quality, emotional response, monetary price, behavioural price, and reputation”. 22 items were used to measure service quality. All items were on 7-point Likert scale. Part 3 consists of 5 items. These items were related with age, occupation, monthly income, overall satisfaction, and revisit intention.

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2.2 Research Design and Sample Self-administered questionnaire utilizing questionnaires, research was conducted. To examine questionnaires, pilot testing was performed. The responders of pilot testing were consumers of trekking operators. After this testing, certain words and phrases were adjusted to improve comprehension. A sample of 232 clients was collected from 12 operators of hiking trails in the Kundasang, Sabah region. Kundasang is a town in the Ranau district of Sabah, Malaysia, which is situated along the Kundasang Valley. It is around 6 kms from Kinabalu National Park and 12 kms from Ranau. It provides a panoramic view of Mount Kinabalu and is the nearest settlement to the mountain. When registering with the operators, the questionnaire was handed to all clients of the hiking trail.

3 Data Analysis Statistical Process for Social Sciences (SPSS) version 28 were used for data analysis purpose. Anova and Regression test were used to check differences and relationship of variables.

3.1 Anova Analysis One way ANOVA test (Table 1) shows that there is a difference among age groups. Revisit and service convenience is equally important for all age groups. Post-hock LSD test shows that the difference in revisit and service consistency exists in 50 above age groups. Table 1 One way ANOVA

Age

Occupation

Monthly income

Sig

Sig

Sig

Overall satisfaction

0.321

0.364

0.123

Revisit intentions

0.031

0.545

0.431

Perceived functional value

0.123

0.421

0.234

Perceived symbolic value

0.216

0.512

0.233

Service consistency

0.354

0.274

0.132

Service convenience

0.045

0.213

0.321

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3.2 Regression Analysis Perceived value has a strong correlation with all aspects of service quality. Value aspects were viewed as dependant on the quality of service. There are substantial relationships between all variables in a multivariate test. Regression is used to examine the link between service quality and functional value (Table 2). These variables have an r-squared value of 0.563, which indicates a strong correlation between them. However, once again, there is a negative correlation between service convenience and functional value. Similar findings have been found in a regression test of symbolic value and service quality components. The correlation is strong, and the r-square value (0.493) indicates an excellent fit. First of all, the VIF values are low enough to prove that there is no multi-linearity issue. The dimensions of perceived value and quality of service have a negative correlation, hence, there is no correlation between the two. Regression analysis of satisfaction with perceived value components revealed a strong and positive correlation (Table 3). The second value of r-square is sufficient to demonstrate a reasonable model fit. The link between perceived value aspects and satisfaction is favourable. There is only a significant relationship between service consistency and satisfaction, but there is a positive relationship between all variables. Satisfaction and the quality of the service have a positive relationship. There is a positive link between how valuable something is seen to be and how likely someone is to come back. The results of the regression show that the relationship between satisfaction and plans to come back is strong and positive (sig = 0.000, beta = 10.007). The value of r-square is 0.453, and satisfactions are the only independent variable. So, the model fits well and proves our theory that there is a strong link between wanting to come back and being happy. If people are happy, they are more likely to want to come back. Table 2 Relationship between service quality dimensions and perceived value dimensions Source

Dependent variable

Type III sum of squares

Df

Mean square

F

Sig

Service consistency

Functional value

65.854

1

64.741

122.345

0.000

Symbolic value

25.543

1

25.423

65.345

0.000

Functional value

9.543

1

7.564

15.114

0.000

Symbolic value

17.654

1

15.435

42.432

0.000

Service convenience

aR bR

squared = 0.632 (adjusted R squared = 0.641) squared = 0.393 (adjusted R squared = 0.350)

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Table 3 Overall satisfaction Unstandardized coefficients

Standardized coefficients

B

Std. error

Beta

(Constant)

1.001

0.302

3.316

0.001

Functional value

0.305

0.104

0.268

2.927

Symbolic value

429

0.132

0.297

3.248

a Dependent

t

Sig

Collinearity statistics Tolerance

VIF

0.004

0.744

1.344

0.002

0.744

1.344

variable: overall satisfaction

4 Discussion and Conclusion Service quality is an evaluation of whether the service provided meets the needs and expectations of customers. To improve customer retention and service convenience, businesses must conduct research on other age groups. This study investigates the relationship between service quality, perceived value, satisfaction, and intention to return in the hiking sector. First, there is a considerable link between service quality measures and perceived value dimensions. However, only one factor (service consistency) demonstrates a positive correlation. Then, we discover that perceived value is significant and has a good association with contentment, and we individually reconsider our aims. Individually considered, symbolic value is more essential than functional value in revisit intents. The association between service quality and satisfaction and inclination to return is positive and significant. However, one factor has a significant impact, and that is service constancy. It is abundantly clear that consistent services increase customer satisfaction and repeat visits. Relationships characterized by gratification and recurrence were confirmed to be favourable. Importantly, both pleasure and perceived value have strong and positive relationships with intentions to return. But the relationship between contentment and perceived value is more intense. What is the customer quality and satisfaction requirement for developing sustainable tourism in Kundasang through hiking? This has implications for both the managers and owners of hiking operations.

References Akbaba A (2006) Measuring service quality in the hotel industry: a study in a business hotel in Turkey. Hosp Manage 25:170–192 Bowler DE, Buyung-Ali LM, Knight TM, Pullin AS (2010) A systematic review of evidence for the added benefits to health of exposure to natural environments. BMC Public Health 10:456 Chhetri P, Arrowsmith C, Jackson M (2004) Determining hiking experiences in naturebased tourist destinations. Tour Manage 25:31–43

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D’Antonio A, Monz C, Newman P, Lawson S, Taff D (2012) The effects of local ecological knowledge, minimum-impact knowledge, and prior experience on visitor perceptions of the ecological impacts of backcountry recreation. Environ Manage 50:542–554 Den Breejen L (2007) The experiences of 7 long-distance walking: a case study of the west highland way in Scotland. Tour Manage 28(6):1417–1427 Eastep BT, Goldenberg M (2008) Going hiking and backpacking. In: Goldenberg M, Martin B (eds) Hiking and backpacking. Human Kinetics, Champaign, IL, pp 3–21 Fredman P, Tyrväinen L (2010) Frontiers in nature-based tourism. Scandinavian J Hosp Tour 10(3):177–189 Hairom N (2020) Pendaki bukan sekadar jadi pelancong gunung. Analisis Sinar. https://www.sin arharian.com.my/article/61373/Analisis-Sinar/Pendaki-bukan-sekadar-jadipelancong-gunung Kay G, Moxham N (1996) Path for whom? Countryside access for recreational walking. Leis Stud 15(3):171–183 Lee SA, Manthiou A, Chiang L, Tang LR (2017) An assessment of value dimensions in hiking tourism: pathways toward quality of life. Int J Tour Res 20(2):236–246 Mason RC, Suner S, Williams KA (2013) An analysis of hiker preparedness: a survey of hiker habits in New Hampshire. Wild Environ Med 24(3):221–227 Nasir MNM, Mohamad M, Ghani NIA, Afthanorhan A (2020) Testing mediation roles of place attachment and tourist satisfaction on destination attractiveness and destination loyalty relationship using phantom approach. Manage Sci Lett 10(2):443–454 Nordin MR, Jamal SA (2021) Hiking tourism in Malaysia: origins, benefits and post Covid-19 transformations. Int J Acad Res Business Soc Sci 11(13):88–100 Parasuraman A, Zeithaml VA, Berry LL (1985) A conceptual model of service quality and its implications for future research. J Market 49(4):41–50 Petrick JF (2004) First timers and repeaters perceived value. J Travel Res 43:29–83 Prebensen NK, Woo E, Chen JS, Uysal M (2012) Experience quality in the different phases of a tourist vacation: a case of Northern Norway. Tour Anal 17(5):617–627 Prebensen NK, Wu E, Uysal M (2015) Cocreation as moderator in value experience—satisfaction relationship. J Travel Res 1–12 Smith M, Puczko L (2014) Health, tourism and hospitality: Spas, wellness and medical travel, 2nd edn. Routledge, London Wöran B, Arnberger A (2012) Exploring relationships between recreation specialization, restorative environments and mountain hikers’ flow experiences. Leisure Sci 34:95–114 (2012)

Effect of the HoPA Program on Body Mass Index and Physical Activity Level Among Children Wan Mohd Norsyam, Nurul Diyana Sanuddin, Norlaila Azura Kosni, Mohd Zulkhairi Mohd Azam, and Maisarah Mohd Saleh

Abstract Children’s activities have been hampered by the COVID-19 pandemic, and they are unable to participate in both outdoor and indoor activities. Furthermore, children’s learning activities are impacted and must be conducted through virtual schooling (PDPR). As a consequence, a systematic approach to promote children’s physical activity while reducing parental strain during PDPR should be designed. The fundamental objective of this study was to see how efficient Home-Based Physical Activity (HoPA) approach in reducing body mass index and promoting physical activity among children. Three (3) types of physical fitness activities and three (3) skill related fitness activities were included in HoPA program. The participants were randomly selected among primary school children. They were asked to complete HoPA program within six weeks duration of intervention. A pre- and post-control group design was used in this study. A total number of 100 children, both boys and girls, were chosen as part of the study sample. There were 50 students in the treatment group and 50 students in the control group participated in the study. All children completed an online survey which included a set of questionnaires to measure their own level of physical activity (PAQ-C) during the lockdown period. Despite controlling for pre-scores after completing HoPA program, two-way ANCOVA analysis revealed significant differences in mean post-scores for body mass index (p < 0.01) and physical activity (PAQ-C) (p < 0.01) between treatment groups for male and female students. In contrast to the group of children who attended Physical Education class as normal, the HoPA program offered a good and significant change to the children who received the program intervention. The study’s findings indicate that using HoPA program can encourage children to participate in physical activities, which can promote their level of physical activity. Keywords Physical education · Physical activity · HoPA program (home-based physical activity)

W. M. Norsyam · N. D. Sanuddin (B) · N. A. Kosni · M. Z. M. Azam · M. M. Saleh Universiti Teknologi MARA (Pahang), Pahang, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_13

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1 Introduction The current coronavirus disease outbreak in 2019 (COVID-19) started in Wuhan, China, and later expanded to the entire world, resulting in 353,000 cases and 15,000 fatalities (Carrillo and Flores 2020; Guan et al. 2020), including Malaysia. The Malaysian government has implemented the Movement Control Order (MCO) on March 18, 2020 throughout Malaysia. MCO mandated the closure of all government sectors and private offices including education sector to curb the spread of viruses (Baiyere and Li 2016; Krejcie and Morgan 1970). Due to these causes, the teaching process must be continued in order to prevent students’ learning processes, particularly those of primary school kids, from falling far behind. Education is one of the essential components important for the development of a country as it will produce a qualified and knowledgeable labor force (Carrillo and Flores 2020). The health benefits of physical activity are numerous, however, during this COVID-19 pandemic, many activities were prohibited, including access to schools, workplaces, recreational, and sporting facilities, which were temporarily closed. As a result, the vast majority of kids may be attributed to the lack of equal opportunities to participate in physical activity (PA) and the unavailability of sports facilities caused by school closures. Teenage years are crucial for the development of healthrelated behaviors and the encouragement of PA. Moreover, the lockdowns have had an impact on people’s jobs, education, travel, and leisure activities, as well as their levels of physical activity (PA) and sedentary behavior (SB) (Carrillo and Flores 2020; Naderipour et al. 2020). Global shifts in economic and sociodemographic development have resulted in dietary and lifestyle changes that have implications for the nutrition and health status of every individual including children around the world. The problem of overweight in children is one of the physical problems that often get public attention and can affect other health problems such as the risk of heart disease, diabetes, blood pressure instability, and hypertension (Carrillo and Flores 2020; Fu et al. 2016; McKenzie et al. 2016). Sedentary behavior and physical activity have both been greatly influenced on body mass index, mental, and physical health. The results of a survey used to gauge the precise effect of this limitation on movement patterns revealed a marked decline in total levels of physical activity as well as an increase in sedentary time. Consequently, the government has adopted home-based learning (HBL). Through electronic/technological means, it subtly transforms the conventional educational model into the contemporary learning model. Due to the extent to which e-learning might expand, it can be categorized as either synchronous or asynchronous. Therefore, e-learning is covered under a broader definition of technology-based learning through websites, learning portals, video conferencing, YouTube, mobile apps, and thousands of different free websites available for blended learning tools (Carrillo and Flores 2020; Chambonniere et al. 2021; Jiménez-Pavón et al. 2020). Since teachers had to convert in-person learning, whether theoretically or practically, into an online system during the pandemic crisis, there was a deficiency in the delivery of knowledge, particularly regarding practical implementations like physical

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activity. To increase physical fitness and health, a systematic and effective Physical Education curriculum must be developed that is suitable for the age of primary school students (Chambonniere et al. 2021; Fu et al. 2016; McKenzie et al. 2016). However, there is still a paucity of study and literature on children’s physical activity during this pandemic in Peninsular Malaysia. Based on the findings, this study intended to clarify the effect of Home-based Physical Activity (HoPA) on body mass index and physical activity level among school children. HoPA embedded ecological model, social theory, and cognitive social theory. The ideas have been utilized in this program’s material to create a productive teaching and learning environment.

2 Methodology Research Design The design used in this study was a cross-sectional study which focusing on school children aged between nine to eleven years old. This study was designed to explore the mean differences between level of physical activity and body mass index for both genders. Participants were recruited from two selected primary schools and with the consent of parents/guardians. Participants were briefed verbally regarding the procedures during the first meeting. The protocol and potential advantages were explained to the participants before they were given the consent form to be filled by their parents or guardian. The approval was obtained from the Education Planning and Research Department (EPRD), Ministry of Education Malaysia, and the State Education Department as well as the school authorities prior to data collection. Research Participants Participants were divided into two groups (control and treatment groups). Participants in treatment group undergo their Physical Education teaching session using HoPA’s approach, while participants in control group undergone their routine Physical Education teaching session. A pre-test was conducted on the school children prior to the treatment. The selection of participants was based on the ’intact sampling’ method which is in the condition that all students found in both classes are kept as study subjects. The appropriate sample size for this study was 100 participants based on the rules used to determine sample size in multivariate regression (50 + 8 * number of variables) (Fidell et al. 2013). Research Variables i. Body composition Body mass index (BMI) was used in order to determine body compositions for all participants. The participant’s height and weight were recorded in the units of meter and kilogram, respectively. The obtained values the were then transform into formulation of body mass index to obtain the BMI value in the unit of kg/m2 .

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ii. Physical Activity Questionnaire for Older Children (PAQ-C) The Physical Activity Questionnaire for Older Children (PAQ-C) is a widely used, self-administered, 7-day recall instrument. It was developed to assess general levels of physical activity throughout the elementary school year for students aged 8–14 years old (Guan et al. 2020). In Malaysia, primary school children aged 7–12 years old are eligible to answer this questionnaire with students aged below than 10 years old are being proxy-reported by their parents or legal guardian (Patrick et al. 2006). This questionnaire consists of 9 questions about sports and games, physical activities in school, and leisure. Each is worth 1 (did not practice any activity) to 5 (practiced activities on all weekdays) and the final score is the average of the questions. In the end, the mean score of the 9 items of questions was classified as: < 2.04 = ‘low activity’, 2.04 − < 2.9 = ‘moderate activity’, ≥ 2.9 ‘high activity’ (Zaki et al. 2016). The item scale correlations were all above 0.30, and the scale reliability was acceptable for both females (α = 0.83) and males (α = 0.80) (Guan et al. 2020). The test–retest reliability for the PAQ-C ranged from r = 0.75–0.82, and internal consistency reliability values (coefficient alpha) indicate good value that ranged from 0.81 to 0.86 (Zaki et al. 2016). This questionnaire is widely used in research, in order to assess physical activity level of large and small populations at minimal cost (Zaki et al. 2016). The questionnaire was administered in bilanguages (English and Bahasa Malaysia). iii. Home-based Physical Activity (HoPA) The HoPA program was created by the researchers in this study by adapting some of the instruments already in use by earlier researchers in the setting of the study population. The HoPA program had being developed by the expertise with a sports science background that emphasizes physical fitness and motor abilities. According to Tuckman (1978) (Tuckman 1999; Tuckman and Harper 2012), a value of 0.60 is considered to have mastered or achieved a high level of achievement. Therefore, the results of expert evaluation of the content of the HoPA’s program have a high content validity value of 0.86. Therefore, this value can explain that the content of the HoPA’s program is very relevant to be used in the learning and teaching process for the subject of Physical Education and Health, and it is very suitable for use in the present study. HoPA is a self-management program. It includes receiving instruction and practice in self-monitoring, goal setting, controlled behavior, stimulus control, selfreinforcement, self-direction, scheduling, problem solving, and decision making. It is designed to teach children behavior change skills believed to be important in the generalization and maintenance of regular physical activity. There are six (6) proposed activities for Physical Education learning activity that involved total of six essential elements of mental and body health wellness namely, fundamental motor skill, cognitive, movement knowledge, fitness/wellness, healthy lifestyle, and emotional/enjoyment (Fig. 1). Children then need to comprehend and study each exercise performed to improve physical fitness activities and adopt a lifestyle using the previously learned knowledge and skills. The researchers choose six (6)

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Fig. 1 Connectivity between the activities and essential element for mental and physical wellness

different types of activities for this program based on physical fitness activities and skill-building activities. Based on the researcher’s area of expertise, activities and techniques were chosen for this program to have a good impact on learning. Research Procedure The researcher divided participants into two groups, one group is the treatment group, and the other group is the control group. Prior to the group assignments, a pre-test was conducted via answering a questionnaire of (PAQ-C) and measuring body mass index among participants. On the other hands, the treatment group requires participants to undergo the HoPA program for six (6) weeks (PDPR). Meanwhile participants in control group were required to undergo Physical Education and health learning sessions as usual. Post-test measurements of PAQ-C and BMI were conducted at the end of 6 weeks after the interventions period. Statistical Analysis In this study, the researcher used the computer software Statistical Package for the Social Science for Window 20.0 (SPSS). The data obtained will be analyzed using descriptive statistical analysis and inferential statistical analysis. In this study, descriptive statistical analysis such as mean, standard deviation, and percentage was used to get a true picture of the study sample’s demographic data, body mass index, and physical activity level. Analysis of Covariance (ANCOVA) statistical analysis was used to answer the research question.

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3 Result The two-way ANCOVA analysis in Table 1 showed there was a major effect of the independent variable (Gender/Male) which was significant, F (1, 47) = 668.092, p = 0.0001, p < 0.05, eta squared = 0.851 by controlling for the covariate effect. The analysis showed that there was a significant difference in the mean post-score for body mass index between the treatment groups for male students by controlling for the pre-score of body mass index after going through the HoPA program. The analysis showed that there was a very high (r = 0.99) and significant correlation between the pre-test score of body mass index before the intervention with the posttest score for the body mass index test after the intervention. Furthermore, the results of the two-way ANCOVA analysis in Table 1 also shows that there is a main effect of the independent variable (Gender/Male) is significant, F (1, 47) = 175.485, p = 0.0001, p < 0.05, eta squared = 0.600 by controlling for the effect of covariates. The analysis showed that there was a significant difference in the mean post-score for level of Physical Activity (PAQ-C) between the treatment groups for male students by controlling for the pre-score of level physical activity after going through the HoPA program. A total of 54% of the total variance could be explained, when controlling for the effect of pre-scores for level of Physical Activity (PAQ-C) after being given the HoPA program intervention on the achievement of post-scores for levels in Physical Activity (Fig. 2). The two-way ANCOVA analysis in Table 2 showed that there was a main effect of the independent variable (Gender/Female) was significant, F (1, 47) = 628.166, p = 0.0001, p < 0.05, eta squared = 0.843 by controlling covariate effect. The analysis showed that there was a significant difference in the mean post-score for body mass index between the treatment groups for female students by controlling for the prescore of body mass index after going through the HoPA program. The analysis showed that there was a very high (r = 0.99) and significant correlation between the pre-test score of body mass index before the intervention with the post-test score for the body mass index test after the intervention. Furthermore, the results of the two-way ANCOVA in Table 2 also show that there is a main effect of the independent variable (Gender/female) is significant, F (1, 47) = 363.741, p = 0.0001, p < 0.05, eta squared = 0.757 by controlling for the covariate effect. The analysis showed that there was a significant difference in the mean post-score for level of Physical Activity (PAQ-C) between the treatment groups for female students by controlling for the pre-score of Physical Activity (PAQ-C) after going through the HoPA program. A total of 66% of the total variance could be explained, when controlling for the effect of the pre-test of Physical Activity score after being given the HoPA program intervention on the achievement of the post level of Physical Activity score.

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Table 1 Two-way ANCOVA analysis of body mass index, physical activity level (tests of betweensubjects effects—male) Source Corrected model

Type III sum of squares

Df

Mean square

F

Sig.

Partial eta squared

4742.919

2

2371.459

11,989.953

0.000

0.995

Intercept

0.053

1

0.053

0.269

0.605

0.002

Pre-BMI

4671.832

1

4671.832

23,620.494

0.000

0.995

132.140

1

132.140

668.092

0.000

0.851

0.198

Group Error

23.141

47

Total

43,004.432

50

4766.060

49

Corrected total Corrected model Intercept Pre (PAQ-C)

11,312.633

2

5656.317

154.013

0.000

0.725

746.775

1

746.775

20.334

0.000

0.148

5059.630

1

5059.630

137.766

0.000

0.541

175.485

0.000

0.600

Group

6444.875

1

6444.875

Error

4296.958

47

36.726

Total

1,137,523.000

50

15,609.592

49

Corrected total

squared = 0.995 (adjusted R squared = 0.995) b R squared = 0.901 (adjusted R squared = 0.899) c R squared = 0.725 (adjusted R squared = 0.720) d Computed using alpha = 0.05 aR

Fig. 2 Box plots of physical activity level between subject effect (male)

1400 PA-2

1200 1000 800 600 400 200

PA-1

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Table 2 Two-way ANCOVA analysis of body mass index and physical activity level (tests of between-subjects effects—female) Source Corrected model

Type III sum of squares

Df

Mean square

F

Sig.

Partial eta squared

6327.201

2

3163.601

20,380.989

0.000

0.997

Intercept

0.309

1

0.309

1.990

0.161

0.017

Pre-BMI

6320.870

1

6320.870

40,721.189

0.000

0.997

97.506

1

97.506

628.166

0.000

0.843

Error

18.161

47

0.155

Total

62,000.454

50

6345.362

49

14,545.565

2

7272.782

233.612

0.000

0.800

246.817

1

246.817

7.928

0.006

0.063

7101.608

1

7101.608

228.114

0.000

0.661

363.741

0.000

0.757

Group

Corrected total Corrected model Intercept Pre-PAQ-C Group

11,323.935

1

11,323.935

Error

3642.427

47

31.132

Total

1,143,585.000

50

18,187.992

49

Corrected total

squared = 0.997 (adjusted R squared = 0.997) b R squared = 0.963 (adjusted R squared = 0.963) c R squared = 0.800 (adjusted R squared = 0.796) d Computed using alpha = 0.05 aR

4 Discussion The primary hypothesis of the study was to identify the effect of Home-based Physical Activity (HoPA) on body mass index and level of physical activity among school children. The result of study indicates a positive effect on body mass index. It suggests that this home-based intervention approach may also improve the children’s body composition and adiposities. These findings are consistent with Patrick et al. (2006) showed there were improvement in body fat percentage where greater improvements shown in body composition, as measured by a bigger reduction in both the percentage of total body fat and fat mass. The data has important implications for public health, particularly with regard to the promotion of healthy body weights, given that obesity in childhood can be tracked at early stage throughout development into adulthood. The results of the analysis show that there is a high and significant difference on the change in body mass index and level of physical activity for boys and girls in the treatment group who received the intervention of the HoPA program for six weeks compared to boys and girls from the group control. Therefore, this shows that the intervention program through the HoPA program can help improve the physical activity level of the study subjects. This difference explains that the HoPA program can have a positive effect on changes in body composition, and improvement in

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physical activity level among boys and girls in the treatment group compared to boys and girls in the control group. The findings of the analysis obtained are almost in line with the findings of the study obtained by Fu et al. (2016) (McKenzie et al. 2016), who stated that the structured educational module has a significant effect on changes in physical activity and motivation during physical activity among boys and girls. In addition, this statement is also supported by the findings of previous researchers who explained that there was a significant difference in the changes between the treatment group and the control group for pre- and post-tests, on all variables after the subjects underwent the intervention program (McKenzie et al. 2016).

5 Conclusion In conclusion, the results of this study provide a very unique insight into the effectiveness of the HoPA program and provide a positive impact on changes in body mass index, and level of physical activity among children. The results of this study are to cover the context of the curriculum, program activities, program development innovations that have been carefully planned and the consistent involvement of students in each activity that has been carried out by researchers to promote a healthy lifestyle. The HoPA program is one of the programs that can improve physical fitness and health either during the Physical Education subject or even after school hours. The study also showed that the activities that were implemented in the HoPA program, which was conducted for six weeks were effective in reducing body mass index, attracting children to do physical activities. However, the problem of overweight and physical fitness among children today is still at an alarming level. The dependence of today’s society on automated machines and systems in daily life affects the problem of inactivity to perform physical activities as well as exercise.

References American College of Sport Medicine (2010) Guidelines for exercise testing and prescription, 8th edn. Lippincott Williams & Wilkins, Baltimore Baiyere A, Li H (2016) Application of a virtual collaborative environment in a teaching case. In: AMCIS 2016: surfing the IT innovation wave—22nd Americas conference on information systems Carrillo C, Flores MA (2020) COVID-19 and teacher education: a literature review of online teaching and learning practices. Eur J Teach Educ 43(4):466–487 Chambonniere C, Lambert C, Fearnbach N, Tardieu M, Fillon A, Genin P, Duclos M et al (2021) Effect of the COVID-19 lockdown on physical activity and sedentary behaviors in French children and adolescents: New results from the ONAPS national survey. Europ J Integr Med 43:101308 Fidell S, Tabachnick B, Mestre V, Fidell L (2013) Aircraft noise-induced awakenings are more reasonably predicted from relative than from absolute sound exposure levels. J Acoust Soc Am 134(5):3645–3653

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Fu Y, Gao Z, Hannon JC, Burns RD, Brusseau Jr, TA (2016) Effect of the SPARK program on physical activity, cardiorespiratory endurance, and motivation in middle-school students. J Phys Activity Health 13(5) Gavin J, Keough M, Abravanel M, Moudrakovski T, Mcbrearty M (2014) Motivations for participation in physical activity across the lifespan. Int J Wellbeing 4(1) Guan W, Ni Z, Hu Y, Liang W, Ou C, He J, Liu L, Shan H, Lei C, Hui DSC, Du B, Li L, Zeng G, Yuen KY, Chen R, Tang C, Wang T, Chen P, Xiang J, Li S (2020) Clinical characteristics of coronavirus disease 2019 in China. New England J Med 382(18). https://doi.org/10.1056/nej moa2002032 Jiménez-Pavón D, Carbonell-Baeza A, Lavie CJ (2020) Physical exercise as therapy to fight against the mental and physical consequences of COVID-19 quarantine: special focus in older people. Prog Cardiovasc Dis 63(3):386 Kowalski KC, Crocker PRE, Faulkner RA (2004) The validity of the physical activity questionnaire for older children (PAQ-C). Med Sci Sports Exerc 27(Supplement):S115. https://doi.org/10. 1249/00005768-199505001-00651 Krejcie RV, Morgan DW (1970) Sample size determination table. Educ Psychol Measur 30:607–610 Lounsbery MA, McKenzie TL (2020) American kinesiology association’s role in promoting school physical activity policy. Kinesiol Rev 9(4):313–318 McKenzie TL, Sallis JF, Rosengard P, Ballard K (2016) The SPARK programs: a public health model of physical education research and dissemination. J Teach Phys Educ 35(4):381–389 Naderipour A, Abdul-Malek Z, Ahmad NA, Kamyab H, Ashokkumar V, Ngamcharussrivichai C, Chelliapan S (2020) Effect of COVID-19 virus on reducing GHG emission and increasing energy generated by renewable energy sources: A brief study in Malaysian context. Environ Technol Innov 20:1–8 Patrick K, Calfas KJ, Norman GJ, Zabinski MF, Sallis JF, Rupp J, Cella J et al (2006) Randomized controlled trial of a primary care and home-based intervention for physical activity and nutrition behaviors: PACE+ for adolescents. Arch Pediatrics Adoles Med 160(2):128–136 Pavon DJ, Baeza AC (2020) Physical exercise as therapy to fight against the mental and physical consequences of COVID-19 quarantine: Special focus in older people. Prog Cardiovasc Dis 63:386–388 Shahzad A, Hassan R, Aremu AY, Hussain A, Lodhi RN (2020) Effects of COVID-19 in E-learning on higher education institution students: the group comparison between male and female. Qual Quant 1–22 Stockwell S (2021) Investigating digital behaviour change interventions for physical activity and sedentary behaviour in socially isolated older adults (Doctoral dissertation, Anglia Ruskin University) Teixeira PJ, Carraça EV, Markland D, Silva MN, Ryan RM (2012) Exercise, physical activity, and self-determination theory: a systematic review. Int J Behav Nutr Phys Act 9(1):1–30 Tuckman BW (1999) Conducting educational research, 5th edn. Harcourt Brace College, Orlando Tuckman BW, Harper BE (2012) Conducting educational research. Rowman & Littlefield Publishers Williams AS, Ge B, Petroski G, Kruse RL, McElroy JA, Koopman RJ (2018) Socioeconomic status and other factors associated with childhood obesity. J Am Board Family Med 31(4):514–521 Wong JE, Parikh P, Poh BK, Deurenberg P (2016) Physical activity of Malaysian primary school children. Asia Pacific J Public Health 28(5):35S46S. https://doi.org/10.1177/101053951665 0726 World Health Organisation (2012) Measurement of and target setting for well-being: an initiative by the WHO Regional Office for Europe. Second meeting of the expert group Paris Zaki NAM, Sahril N, Omar MA, Ahmad MH, Baharudin A, Mohd Nor NS (2016) Reliability and validity of the physical activity questionnaire for older children (PAQ-C) In Malay Language. Int J Public Health Res 6(1):670–676. http://journalarticle.ukm.my/9697/

Relationship of Personality Traits and Competitive Trait Anxiety in Recreational Individual Event Sports Kleven Jin Yew Lim and Kang Mea Kee

Abstract Competitive anxiety is a negative emotional feeling that severely impairs sports performance when competing in sports. Some studies indicated that specific personality traits might have an influence on the development of depressive and anxiety symptoms, especially in individual sports athletes. Nevertheless, the influence of personality traits on competition anxiety is still not clearly understood. This study was conducted to investigate the relationship between personality trait and competitive anxiety among students who enrolled in the co-curriculum program in individual sports, specifically in badminton, swimming, squash, tennis and taekwondo. Two hundred and forty-three recreational college participants competing in the co-curriculum program participated in this study. Personality characteristics and competitive anxiety were assessed using the Big Five Inventory and Sports Anxiety Scale-2, respectively. Relationships between personality and competitive anxiety were analyzed using Pearson product-moment correlation coefficient. Additionally, multiple regression analysis was used to measure the contributions of personality on competitive anxiety. The correlation analysis showed that only extraversion (r = − 0.212, p = 0.001) and neuroticism (r = 0.486, p < 0.001) were significantly correlated with competitive anxiety. Multiple regression analysis revealed the neuroticism (β = 0.540) and conscientiousness (β = 0.157) had positive effects on competitive anxiety, predicting 25.9% of the variance explained. The findings concluded that even though personality traits can be used to predict to competitive anxiety in individual sports athletes, only neuroticism and conscientiousness were significantly positive predictors of competitive anxiety. In addition, gender did not moderate the relationships between the dimensions of personality traits and competitive anxiety. Hence, coaches can implement early stress-coping intervention based on their athletes’ personality traits and manage their instructional strategies to help athletes reduce mental stress during competition to achieve their full potential. K. J. Y. Lim (B) · K. M. Kee Tunku Abdul Rahman University of Management and Technology, Kuala Lumpur, Malaysia e-mail: [email protected] K. M. Kee e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_14

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Keywords Personality traits · Competitive trait anxiety · Recreational athletes

1 Introduction Physiological and psychological abilities of elite athletes are critical determinants to sporting success (McCrae and Costa 1999). Predicting success in sports can be quite a daunting task as every top athlete has a specific physical, psychological and sociological make-up, depending upon the type of sport, the age factor, the training received. However, experts observed that most successful athletes share similar behavior, responses and character that are distinctive from less successful athletes (Bali 2015). This led to many believing that personality trait is an important factor that influence these psychological abilities. Personality traits are considered to be unique because they evolved on a variety of factors such as individual experiences, background, gender and perception. According to McCrae and Costa (1999), the personality traits are bipolar and follow a normal distribution, where most people score in the middle of the scale with few scoring at the extremes. The Big Five consists of five broad trait dimensions that make up the basic tendencies: Extraversion, Agreeableness, Neuroticism, Conscientiousness and Openness of Experience (Intellect). These five dimensions are the central components of personality, and it is able to predict one’s behavior. Extraversion is associated with affectionately, cordiality and sociability; Agreeableness describes the degree of cooperativeness, compliance-ness or humility; Neuroticism relates to anxiety, emotional and vulnerability to stress-related disorder; Openness to Experience distinguishes individuals who prefer variety from those who prefer closure and comfort with familiarity; and Conscientiousness describes disciplinary, orderly and consistency (McCrae and Costa 1999). In sports, anxiety is defined as the stressful response to a certain situation where athletes’ skills are tested (Weinberg and Gould 2019) and it can significantly influence the success of sports performance. Sports anxiety can be divided into trait anxiety and state anxiety, with both somatic (physiological) and cognitive (psychological) components (Jouvent et al. 1999). Trait anxiety is a personality trait that describes individual differences related to the likelihood that a person will experience anxiety. In contrast, state anxiety is an unpleasant psychophysiological state in certain threatening situations (Leal et al. 2017). Somatic anxiety is characterized by physiological responses such as sweaty palms and increased heart rate. Meanwhile, cognitive anxiety is characterized by nervousness, negative thoughts and worrying (Weinberg and Gould 2019). Individuals with high trait anxiety have a greater tendency to experience state anxiety. There are several models that explain the relationship between anxiety and performance. Although experiencing some degree of anxiety may facilitate performance, most theories agree that high levels of anxiety can have detrimental effects on sports performance.

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Athletes participating in individual event sports are more prone to anxiety and depression compared to team sports athletes. Pluhar et al. (2019) reported that individual sports athletes suffered more from competitive anxiety that is linked to depressive symptoms. The development of depressive and anxiety symptoms might be influenced by specific personality traits. In addition, the relationship of personality traits on competitive trait anxiety is also unclear due to very limited study done. Most of the studies of personality traits on competitive anxiety found were conducted on elite team sports athletes in the Western countries (Kemarat et al. 2022). To date, there is a lack of research in individual sports, especially at the recreational level, that examines the relationship between personality traits using the five-factor model and competitive trait anxiety in Asian collegiate athletes. In response to the uncertain information from previous research, this study was carried out to examine the relationship between personality trait and competitive trait anxiety among individual sports athletes.

2 Methodology This study was a non-experimental study using the correlational technique to determine the relationship between personality traits and competitive trait anxiety. The participants were first briefed on the purpose and procedures with the permission of the respective sports coordinators in charge one week prior to their competition day. Overall, the participants took about 15 min to complete the questionnaires.

2.1 Participants A total of 243 participants from Tunku Abdul Rahman University College, KL Main Campus who enrolled in the compulsory college co-curricular program in badminton (n = 82), squash (n = 22), tennis (n = 19), swimming (n = 102) and taekwondo (n = 18) responded to this study.

2.2 Instrumentation Two instruments were adopted to study the relationship between personality traits and competitive trait anxiety. The “Big Five Inventory” (BFI) developed by John and Srivastava (1999) was adapted to measure personality traits, and Sports Anxiety Scale-2 (Smith et al. 2006) was adopted to measure competitive trait anxiety of the participants.

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Big Five Inventory (BFI) developed by John and Srivastava (1999) consists of 44 items that measure the Big Five dimensions of personality, which are Conscientiousness, Agreeableness, Openness to Experience, Extraversion and Neuroticism. A 5-point rating scale was used, ranging from 1 = disagree strongly to 5 = agree strongly. Participants were advised that the questionnaire included a number of characteristics that may or may not apply to them and were asked to select the extent to which they agree or disagree with each statement. Sports Anxiety Scale-2 (SAS-2) was designed by Smith et al. (2006) which contains 15 items to reflect possible responses that young athletes may have before or while they compete in. For each item, college athletes indicated how they typically felt based on a 4-point Likert scale, ranging from not at all (1) to very much (5).

2.3 Statistical Methods SPSS Version 20.00 was used for the data analysis. Descriptive data analysis was used to describe the characteristics of the participants and is expressed in terms of mean and standard deviation. Cronbach alpha reliability test was conducted to test the reliability of the items in the Big Five Inventory and Sports Anxiety Scale-2 questionnaires. Pearson’s correlation coefficient was used to determine the relationship between personality traits with competitive trait anxiety. While the multiple regression analysis was used to determine the predictors of competitive trait anxiety. A pilot study was administered on 30 university students from Tunku Abdul Rahman University College showed that the BFI and SAS-2 had good reliability (α > 0.70).

3 Results 3.1 Correlations Between Personality Traits and Competitive Trait Anxiety Table 1 gives the results of the correlation analysis to determine the relationship between personality traits and competitive anxiety. Overall, only two personality traits (extraversion and neuroticism) had significant correlations with competitive trait anxiety. Meanwhile, agreeableness, conscientiousness and openness did not significantly correlate to competitive trait anxiety. The extraversion subscale and competitive trait anxiety were found to be significantly and negatively correlated, r = −0.212, p = 0.001. Overall, there was a significant weak negative correlation between extraversion and competitive trait anxiety. On the other hand, neuroticism and competitive trait anxiety were found to be significantly, and positively correlated, r = 0.486, p < 0.001.

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Table 1 Summary of the Pearson product-moment correlation coefficient analysis Competitive anxiety

EX

AG

CS

NT

OP

−0.212*

−0.094

−0.099

0.486*

−0.099

* Correlation is significant at the 0.05 level (2-tailed) EX extraversion, AG agreeableness, CS conscientiousness, NT neuroticism, OP openness

3.2 Predicting Competitive Trait Anxiety from Personality Traits Table 2 summarizes the results of the descriptive statistics and analysis results. The multiple regression model with all five personality traits as predictors produced R2 = 0.259, F (5, 237) = 16.566, p < 0.01. The results indicated that the regression model significantly predicted about 25.9% of the variance. As seen in Table 3, Neuroticism (β = 0.540, p < 0.01) and Conscientiousness (β = 0.157, p = 0.018) scales had significant positive regression weights, indicating that individuals with higher scores on these subscales were more likely to experience greater level of competitive trait anxiety after controlling other variables in the model. This explained that neuroticism and conscientiousness offer the strongest unique contribution to predict competitive trait anxiety levels. Meanwhile, Extraversion (β = 0.007, p = 0.916), Agreeableness (β = -0.066, p = 0.294) and Openness (β = -0.070, p = 0.240) did not contribute to the multiple regression model. Table 2 Model of the multiple regression analysis Model

R

1

0.509a

R2

Std. error

0.259

8.13979

Change statistics R2 change

F change

Df1

Df2

Sig. F change

0.259

16.56

5

237

0.001

a

refers to the Predictors: Constant, Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism

Table 3 Summary of the multiple regression analysis between personality traits and competitive anxiety Multiple regression weights Variable

M

SD

Correlation

B

β

Neuroticism

3.21

0.635

0.486

7.955*

0.540

Conscientiousness

3.03

0.443

−0.099

3.314*

0.157

Extraversion

2.86

0.517

−0.212*

0.121

0.007

Agreeableness

3.53

0.467

−0.094

−1.319

−0.066

Openness

3.34

0.507

−0.099

−0.1297

−0.070

*

p < 0.05

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4 Discussion 4.1 Correlation Between Personality Trait and Competitive Trait Anxiety The present study examines the relationship between the five personality traits and competitive trait anxiety levels in college recreational individual event athletes. The results of this study found that there were significant relationships between two of the personality components and competitive trait anxiety among the respondents. As expected, neuroticism (r = 0.486) had the highest positive correlation with competitive trait anxiety. These results are similar with previous studies (Matsutomo et al. 2000; Cerin 2004; Maric 2010; Balyan et al. 2016). A similar study by Balyan et al. (2016) examined the relationship between personality traits with cognitive, somatic anxiety in 50 competitive male athletes reported significant positive relationship between neuroticism and somatic and cognitive anxiety, while negatively correlated with self-confidence. Their study explained that the relationship between personality and competition anxiety may be moderated by self-confidence of the athletes. Neuroticism refers to the likelihood of the athletes to experience negative emotions including anxiety or depression (McCrae and Costa 1999), therefore, athletes with high scores in neuroticism are more likely to have poor emotional stability and thus makes them more vulnerable to anxiety before or during competition, that may significantly affect their sports performance (Piepiora 2021). Petito et al. (2016) examined 130 elite Italian athletes reported similar findings where neuroticism was strongly associated with greater anxiety levels and poorer emotional control. Allen et al. (2011) also found that neurotic athletes had poorer coping strategies and behavior during sports participation, explaining that high levels of neuroticism reduce the tendency and effectiveness of coping strategies during tense situations. The failure to adopt stress-coping strategies may increase the likelihood of the athletes to experience competitive anxiety before or during stressful environments. In this study, most participants were recreational athletes with less than 3 years of competitive experience. This may magnify the effects of neuroticism on competitive trait anxiety due to lack of knowledge and familiarity of using stress-coping mechanisms. These stressrelated vulnerabilities related to neuroticism may influence the sports performance (Bali 2015). Additionally, neurotic athletes also tend to have poorer concentration that may cause them to lose focus on their tasks when performing at highly competitive settings. Glei (2016) explained that neurotic individuals tend to invest most of their limited attentional resources worrying about the past, making it more difficult for them to filter out distractions and focus on the present tasks. Therefore, coaches should keep their instructions clear and simple when dealing with neurotic athletes during high pressure settings because complex phrases may further weaken their concentration levels, which might result in performance deterioration. Moreover, extraversion (r = −0.212) was found to be negatively correlated with competitive trait anxiety, which are again similar to previous studies (Cerin 2004; Mellalieu et al. 2006; Kemarat et al. 2022; Kaplan et al. 2015; Patsiaouras et al.

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2017). Extraversion is characterized by pronounced engagement with the external world (Laney 2002), in which extraverted individuals have high energy and enjoy interaction with other people. Cerin (2004) examined the relationship of neuroticism and extraversion on anxiety revealed a positive correlation between extraversion scores with cognitive anxiety and somatic anxiety. Moreover, their study explained that extraverted athletes perceived physiological symptoms of stress as a tool to facilitate sports performance. Individuals with greater extraversion have a higher tendency to experience positive emotions and minimize negative emotions. This trait allows them to view problematic or threatening situations optimistically that assists their performance (Cerin 2004).

4.2 Predicting Competitive Trait Anxiety from Personality Traits The findings showed that Neuroticism (β = 0.540) and Conscientiousness (β = 0.157) traits were significant predictors of competitive trait anxiety in recreational individual sports athletes. The regression model in this study explained 25.9% of the variances in competitive trait anxiety. As hypothesized, the findings reported that neuroticism had the strongest contribution to competitive trait anxiety. Similarly, previous study conducted on competitive young taekwondo athletes reported that the neuroticism trait predicted 21.22% (Cerin 2004) to 29% (Kemarat et al. 2022) in individual athletes of the total variances of competitive somatic anxiety. As established in previous literature, neuroticism trait is a strong predictor of competitive anxiety because highly neurotic individual experiences more negative emotions, which may also contribute to the occurrence of anxiety or anger symptoms in athletes in stressful situations (Maric 2010; Velikic et al. 2014; Petito et al. 2016; Ford et al. 2017). Athletes with higher neuroticism have poorer emotional stability and control, which significantly increases the risks of experiencing competitive anxiety during highly tense situations (such as competition), and ultimately, may negatively affect tasks performance. Allsop and Gray (2014) and Zinbarg, et al. (2016) suggested that neuroticism increases sensitivity to negativity, which increases the chance of possible mistakes. Interestingly, conscientiousness was also found to be a positive predictor of competitive anxiety. On the contrary, the results in this study contrasted with the findings of Velikic et al. (2014), where they found that conscientiousness did not predict somatic and cognitive competitive anxiety in sports club level athletes in Subotica. Conscientiousness is a personality trait that is linked with displays of self-discipline, high motivation and achievements (Eysenck et al. 1982). The difference may be due to other traits that affect anxiety levels. One of the explanations may be that conscientious individuals have higher motivation and tendency to achieve perfection. Stoeber et al. (2009) noted that conscientiousness and perfectionism are closely associated with each other. Athletes who are highly conscientious have higher expectations and

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put more pressure on themselves, and thus, work hard toward attaining perfection in their performance. Therefore, they are extra worried about making mistakes and errors during high pressured environments because they do not want to disappoint themselves and others. Another study revealed that certain personality traits affect competitive anxiety through training adherence (Matsutomo et al. 2000). In their study, they found that conscientiousness negatively predicts competitive anxiety, while neuroticism positively predicts competitive anxiety in elite judo athletes. Athletes with high conscientiousness have better training adherence, which in turn creates more confidence and less anxiety during performance. Meanwhile, neuroticism might have reversed effects on training that creates lower confidence and greater anxiety (Matsutomo et al. 2000). This study did not support their findings because their study was done on elite athletes with higher training volume and frequency, while the population in this study was recreational athletes with an average frequency of two training sessions per week. Therefore, the positive effects of training adherence may not significantly affect competitive anxiety.

4.3 Moderation Effect of Gender This study found no significant moderation effects of gender on the relationship between the five personality traits with competitive trait anxiety. Perry and Williams (1998) have directly examined gender differences in symptom interpretation and found similar findings to this study. In their comparison of advanced, intermediate and novice male and female tennis players the authors reported no differences in cognitive or somatic anxiety intensity, indicating that gender does not significantly affect the relationship between personality traits and competitive trait anxiety. However, one previous study on Iranian high school students reported a significant moderating effect of gender on some personality traits with state anxiety (Asghari et al. 2013). Their study indicated that gender differences moderated the relationship between extraversion and anxiety in females, and conscientiousness and anxiety in males, suggesting that both personality traits and state anxiety depended on gender differences to a certain degree. The findings in the current study contrasted their study may be due to the difference in study population, where this study focuses on recreational athletes, while their study was done on non-athletes. Moreover, studies have found that female athletes are more extraverted and agreeable compared male athletes, while male athletes had better emotional stability (Weisberg et al. 2011; Patsiaouras et al. 2017).

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5 Conclusion The findings of this study show that personality traits were important in predicting competitive anxiety in athletes participating in individual sports. Among all the personality traits, neuroticism and conscientiousness emerged to be the important predictors in competitive anxiety. From the findings, coaches are able to better predict potential anxiety symptoms and implement early stress-coping intervention based on their athletes’ personality traits. In addition, coaches can also manage their instructional strategies to help athletes reduce mental stress during competition to achieve their full potential.

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Determination of Essential Performance Indicator for Football for Discriminating Between Winner, Draw, and Loser Matches in Malaysia Super League 2021 Muhammad Azim Abdul Rahim, Norlaila Azura Kosni , and Mohamad Nizam Nazarudin Abstract The aims of this study were to (1) determine the essential performance indicator and (2) identify the performance indicators that discriminated between winner, draw, and loser team during Malaysia Super League (MSL) Championship. A total of 38 performance indicators were retrieved from InStat statistic report and notational analysis to check the reliability and validity of the analysis. The principal component analysis (PCA) revealed 20 performance indicators as the essential among the winning team. All the essential performance indicators were then used to discriminate between the winner, draw, and loser matches by using discriminant analysis (DA). The DA discovered that nine out of 20 performance indicators significantly differentiate these three categories of match results with the P value less than 0.05, with 81.37% of sensitivity and sensitivity percentage correct. The significant performance indicators are chances, chances successful, chances (percentage of conversion), shots on target, total number of passes, percentage of accurate passes, key passes, the accurate key passes, and ball possession. All the parameter indicates that the winner team executes significantly higher than the draw and lose team. The outcome of this study may offer the coaches, technical officers, and players a better plan to enhance their team performance. Moreover, the finding provides beneficial information on the characteristics of chances of winning the match. Keywords Malaysia football team · Performance indicators · Multivariate analysis · Technical indicator

M. A. Abdul Rahim Faculty of Sport Science and Recreation, Universiti Teknologi MARA, Shah Alam, Malaysia M. A. Abdul Rahim · N. A. Kosni (B) Faculty of Sport Science and Recreation, Universiti Teknologi MARA, Pahang Branch, 26400 Bandar Tun Abdul RazakPahang, Malaysia e-mail: [email protected] M. N. Nazarudin Faculty of Education, Universiti Kebangsaan Malaysia, Selangor, Malaysia Sabah Football Club, Sabah, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_15

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1 Introduction Research into performance analysis in professional association football has covered a wide range of areas, including performance analysis on the technical, tactical, biomechanical, and physiological aspects. The main objective of these professional clubs has applied this technique to improve performance, which may be part of the why the intensity and performance of the match have improved (Bush 2017). The top level of national soccer competition in Malaysia is Malaysia Super League Championship. This tournament was organized by Football Association of Malaysia with a total of top 12 clubs that eligible and possess the highest point for participating in the league. The players in the club are not restricted to local player but they are number of quotas for import players to play for the club, such as the players from Brazil, Nigeria, and a few other countries worldwide. The rapid development of football in Malaysia encourages the young generation to be a successful football player in future. The government allocated huge amount of funding to development the facility in sport school for grass root talent development as well as provide variety of competition medium in order to inspire people to participate in this sport. To date, football is the one of the most popular sports in Malaysia and the highest paid players. Recently, Malaysia team qualified for AFC Asian Cup 2023 after 42 years. The last achievement was in 1980 where Malaysia qualified on merit for the Asian Cup Finals in Kuwait. Maintaining and enhancing player’s performance are crucial task for the coaches and their support service team. Several factors must take into account when we are dealing with human performance such as psychological readiness, physical capabilities, and skill acquisition. However, limited assessment can be done during actual competition and the performance that we evaluate are technical and tactical indicators. According to Maszczyk et al. (2014), performance indicators known as a set or pattern of action variables that aimed at defining some or all aspects of performance that may contribute to a prosperous outcome (Maszczyk et al. 2014) and needed for evaluating the performance of modern sport (O’Donoghue 2013). As a result, the coaches will employ the performance profiling database to evaluate their players individually or the whole team’s performance. Furthermore, performance profiling could help the coaches to strategize the tactical and technical, make a rational decision to enhance the team performance (Csataljay et al. 2009). This most likely explains the growing study trend and researchers interests in the field of soccer performance analysis, particularly in Malaysia.

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2 Methodology 2.1 Participants and Study Design The participants in this study consist of four top football players from teams competed in the Malaysia Super League in the 2021 season. The total number of 102 matches were in included, and a sum of 38 technical indicators retrieved from InStat® were included in this study. The performance indicators that consist of chances, chances successful, chances % of conversion, fouls, yellow cards, red cards, offsides, corners, shots, shots on target, passes, accurate passes (%), key passes, key passes accurate, crosses, accurate crosses (%), challenges, challenges won (%), defensive challenges, challenges in defence won (%), attacking challenges, challenges in attack won (%), air challenges, air challenges won (%), dribbles, successful dribbles (%), tackles, tackles won (%), lost balls, lost balls in own half, ball recoveries, ball recoveries in opponent’s half, team pressing, pressing efficiency (%), ball possession (%), entrances on opponent’s half, entrances on final third of opponent’s half, and entrances to the opponent’s box were included in soccer performance for Malaysia Super League 2021. InStat® is a private corporation which provides worldwide performance assessment services including the performance of the physical, technical, and tactical performance of the sports team such as basketball, handball, and football. Thus, the indicators proposed are reliable and consistently used by various number of international football team (Kubayi and Toriola 2020). Initially, there are two performance indicator that have been eliminated from the analysis namely total number of goals and InStat® index. The total number of goals significantly differ between the win, draw, and losing team as reported by Kubayi and Toriola (2020). In addition, the number of goals is the result of the game which has been clearly reflected by the category of results viz. win, draw, and lose. The InStat® index was also excluded from main analysis. Previous literature stated that InStat® index was the best discriminator between success and unsuccessful football team. Two performance analysts were assigned to notate the performance of the teams, with each analyst covering a single team at a time. It is worth noting that the analysts were familiarized with the performance metrics chosen before to conducting the comprehensive analysis. To establish consistency and assess the observational mistakes on the created performance indicators, the performance analysts were directed to notate the match separately, and their agreement was then compared. The Cohen’s Kappa statistical test and Cronbach’s alpha analysis were used to assess the analysts’ agreement and consistency with relation to the performance indicators (McGuigan and Hughes 2018). It is worth noting that a Kappa of 0.95 was recorded, as well as a Cronbach’s alpha of 0.97, demonstrating good agreement and consistency among the performance analysts in their overall analysis as well as the data retrieved from InStat® .

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2.2 Principal Component Analysis Principal component analysis is most frequently used identify the pattern of a group of datasets (Musa et al. 2016). In this current study, the principal component analysis was employed to ascertain essential performance indicator among the proposed indicators from InStat® report. The extraction of information from the PCA is accomplished by removing the less significant component from a particular dataset and so retaining the most relevant information from the dataset (Taha et al. 2017a; Abdullah et al. 2016a). A factor loading equal to or higher than 0.70 was considered substantial, and the variable with a value lower than the onset value established was excluded (Razali et al. 2017; Taha et al. 2017b).

2.3 The Application of Discriminant Analysis The discriminant analysis (DA) regulates the variables that distinct among two or more groups. It develops discriminant capacity (DF) in each group. In this study, DA was employed to identify whether the groups differed from the mean of a variable and to use that variable to predict group identity. The use of DA in this current study was to determine which parameter significantly differentiate between the three groups, namely win, draw, and lose.

3 Result and Discussion Figure 1 illustrates the scree plot of the eigenvalue score retrieved from the PCA. The graph shows that the PCA identified a total of 10 components as important in explaining the overall dataset. The eigenvalues greater than one (>1) linked with the components indicate that they are essential. Based on this explanation, the detected components were preserved and afterwards employed as input parameters for additional analysis, i.e. varimax rotation, as indicated by the preceding researchers (Abdullah et al. 2016b). The PCA following the varimax rotation is shown in Table 1. The table shows that the number of key performance indicators is provided for each of the 10 components. These recommended components were found due to the fulfilment of the previously defined predetermined factor loading criterion, i.e. greater, or equal to the 0.70 displayed in bold. It was discovered that the 10 components identified a total of 20 performance indicators out of the 38 initially specified as essential for evaluating performance in football. Key performance indicators identified are chances, chances successful, chances based on percentage of conversion, fouls, shots on target, passes, percentage of accurate passes, key pass, key passes accurate, challenges, percentage of challenges in defence won, attacking challenges, percentage

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Eigenvalue

Cumulative variability (%)

Scree plot

axis

Fig. 1 Scree plot for the eigenvalue and variability of the PCA

of successful dribble, percentage of tackles won, ball recoveries, ball recoveries in opponent’s half, percentage of ball possession, entrances on opponent’s half, and entrances on final third of opponent’s half. The result from discriminant analysis in Table 2 was employed to identify the significant indicator that differentiate between three qualities of result. The precision of quality of result was 81.37% using standard mode method and based on unidimensional test of equality of the means of the classes, revealed a total number of 9 significant performance indicators, i.e. chances, chances successful, chances based on percentage of conversion, shots on target, passes, percentage of accurate passes, key pass, key passes accurate, and percentage of ball possession. Figure 2 demonstrates the box plot to illustrate the comparison between three quality groups based on significant performance indicators. The primary goals of this study were to determine the most essential performance indicators particularly for Malaysia Super League and to distinguish between the team’s quality when they won, drew, and lost games. The findings of these multivariate analyses show that when the sampled team won, they completed significantly more passes and passes in the opposing half than when they lost. The performance indicator that related with chances namely chances, chances success, and percentage of conversion in chances showed that the team have the higher in number and percentage will dominate the game and have the greater probabilities to win the game. There is limited study discussed regarding these indicators where the indicator related with the chances. However, our findings showed, that is, was insignificantly correlated with InStat index (Modric and Jelicic 2022). For the indicator related with passes, explicitly, total passes, accurate passes, key passes, and accurate key passes showed that the winning team overwhelm both draw and lose team. These four performance indicators are essential attribute of successful team. Nevertheless, according to aforementioned study, only accurate passes have significant partial influence the overall InStat index (Modric and Jelicic 2022). The shot on target indicator significantly differentiates between three qualities of game where the winner team have the higher number in shot on target. The current findings in supported by previous study stated that the winning team tent to have more goals, total shots, and shots on target compared to draw and lose teams (McGuigan

0.186 −0.437

−0.113 −0.197 0.440 0.503

Red cards

Offsides

Corners

Shots

0.458 0.896

0.056 −0.014

Accurate crosses, %

0.252

0.764

0.126

−0.088

Attacking challenges

−0.186

0.669 −0.083

0.107

−0.289

Defensive challenges

Challenges in defence won, %

0.042

0.115

0.127

0.159

0.042

0.103

−0.285

−0.019

0.237

−0.053

0.062

−0.012

−0.102

0.651

−0.022

0.091

0.170

−0.109

0.125

0.058

0.100

−0.005

−0.308

0.032

0.046

0.187

−0.256 −0.184

0.144

−0.112

0.090

0.450

0.192

0.096

−0.332

−0.124

−0.021

−0.026

0.087

0.110

D5

−0.120

0.060

−0.156

−0.205

D4

−0.033

0.204

0.204

0.241

0.058

Challenges won, %

Challenges

0.472

Crosses

0.103

−0.066

0.003

0.152

Key passes accurate

−0.145

0.134

Key passes

−0.124

−0.202

0.762

Accurate passes, %

0.719 −0.060

Passes

−0.264

0.251 0.882

Shots on target

−0.024

0.610

0.481

0.180

−0.386

0.032

−0.202

−0.243

0.035

0.209

0.331

0.317

0.080

−0.032

Fouls

Yellow cards

−0.088

0.246

−0.194

0.084 −0.033

Chances successful

0.423

D3

−0.063

D2

Chances, % of conversion

0.234

D1

Chances

Indicators

Table 1 Factor loading value from PCA after varimax rotation

0.122 −0.030

−0.037

−0.033

0.077

−0.040

0.041

0.160

0.896

0.865

0.159

0.093

0.306

0.838

−0.197

0.493

−0.143

0.279

0.000

0.076

−0.005

−0.004

−0.015

−0.097

0.270

0.194

−0.032

0.248

0.088

−0.046

−0.009

−0.042

−0.491

0.244

0.761

D7

−0.100

0.125

0.038

−0.008

−0.055

−0.013

0.044

D6

0.036

0.012

0.064

0.111

0.062

0.071

−0.672

−0.035

0.045

0.114

0.008

−0.033

−0.085

−0.231

−0.118

−0.335

−0.041

−0.053

0.064

−0.038

−0.076

D8

−0.063

0.038

−0.104

0.280

−0.103

−0.095

0.073

0.023

−0.054

0.042

0.122

0.278

−0.139

−0.288

−0.107

−0.010

−0.007

−0.170

0.765

0.831

0.025

D9

(continued)

0.060

0.149

0.234

0.079

0.181

−0.270

−0.088

−0.031

−0.024

0.118

−0.026

−0.031

−0.031

−0.273

0.085

0.193

0.782

0.740

−0.059

−0.037

−0.034

D10

184 M. A. Abdul Rahim et al.

0.107 0.378

0.128 0.167

0.694

−0.354 −0.010

0.436

0.013 −0.405

Successful dribbles, %

0.213 0.048

−0.616

Lost balls in own half

8.834

Eigenvalue 18.635

0.608

Entrances to the opponent’s box 18.635

0.864

Entrances on final third of opponent’s half

Cumulative %

0.913

Entrances on opponent’s half

Variability (%)

0.508 0.922

Team pressing

Ball possession, %

0.385

Ball recoveries in opponent’s half

Pressing efficiency, %

0.080 0.733

Ball recoveries

28.588

9.953

4.348

0.140

0.138

0.094

0.019

0.103

0.073

0.064

0.051

−0.163

0.046 −0.280

Lost balls

Tackles won, %

−0.381 0.064

0.059 0.087 −0.042

−0.395 −0.112

35.221

6.634

3.440

0.365

0.269

0.234

0.116

0.198

−0.152

0.217

−0.155 7.206 42.427

47.851

5.424

2.286

0.007

−0.084 2.785

0.008

0.018

−0.096

−0.147

0.117

0.845

−0.089

0.081

−0.168

−0.059

0.152

0.860

0.271

0.255

−0.120

0.507

0.799

0.071

0.190

−0.019

−0.237

0.418

D5

−0.024

−0.169

0.113

0.407

Dribbles

Tackles

−0.127

0.431 −0.069

0.242

−0.087

−0.104

D4

−0.103

Air challenges won, %

0.021

Air challenges

D3

0.214

−0.004

Challenges in attack won, %

D2

D1

Indicators

Table 1 (continued)

53.500

5.649

1.967

0.006

0.023

0.117

0.042

0.308

0.069

0.115

0.122

−0.104

0.105

0.768

−0.354

−0.133

−0.204

0.176

0.168

−0.079

D6

61.916

8.416

1.778

0.415

0.164

0.068

0.050

0.136

0.015

0.012

0.099

−0.088

−0.202

−0.030

0.056

0.054

0.277

−0.131

−0.173

−0.008

D7

66.127

4.211

1.441

−0.229

71.215

5.088

1.195

0.053

−0.093

−0.016

−0.055 −0.158

−0.045

0.083

0.098

0.128

−0.051

−0.228

−0.015

−0.162

0.259

−0.044

0.081

0.238

−0.183

0.072

D9

−0.006

0.429

0.279

0.153

0.007

0.087

0.009

−0.068

0.007

−0.056

−0.001

0.243

−0.154

0.662

D8

76.744

5.528

1.089

−0.004

−0.042

−0.031

0.035

−0.102

0.383

0.224

0.046

−0.097

−0.119

−0.117

−0.046

−0.021

−0.088

0.483

0.307

−0.107

D10

Determination of Essential Performance Indicator for Football … 185

186

M. A. Abdul Rahim et al.

Table 2 Classification matrix of discriminant analysis (DA) for the performance indicator on the three different results quality Group

% Correct

Group Win

Draw

Lose

Win

65.00%

5

13

2

Draw

63.16%

2

5

12

Lose

92.06%

58

4

1

Total

81.37%

65

22

15

Performance indicators

Lambda

F

p-value

Chances

0.863

7.837

0.001*

Chances successful

0.581

35.685

< 0.0001*

Chances, % of conversion

0.783

13.747

< 0.0001*

Yellow cards

0.973

1.348

0.265

Shots on target

0.912

4.782

0.010*

Passes

0.936

3.370

0.038*

Accurate passes, %

0.902

5.406

0.006*

Key passes

0.891

6.046

0.003*

Key passes accurate

0.897

5.699

0.005*

Challenges

0.960

2.080

0.130

Challenges in defence won, %

0.988

0.614

0.543

Attacking challenges

0.984

0.792

0.456

Successful dribbles, %

0.992

0.383

0.683

Tackles won, %

0.998

0.097

0.907

Lost balls

0.943

2.973

0.056

Ball recoveries

0.947

2.759

0.068

Ball recoveries in opponent’s half

0.971

1.473

0.234

Ball possession, %

0.918

4.445

0.014*

Entrances on opponent’s half

0.961

1.992

0.142

Entrances on final third of opponent’s 0.952 half

2.496

0.088

and Hughes 2018). Nonetheless, contradict with ball possession, most of the teams that had a high percentage of ball possession lost their games. In the current case, it shows a slightly differentiate between winning and drawing team but both winning and drawing team have significantly higher than losing team in ball possession.

Determination of Essential Performance Indicator for Football …

Fig. 2 Box and whisker plots for significant indicators from discriminant analysis

187

188

M. A. Abdul Rahim et al.

Fig. 2 (continued)

4 Conclusion The finding of this current study established that only 20 performance indicators are significant to evaluate the performance of football team competed in Malaysia Super League 2021 and out of 20 indicators, nine indicators significantly differentiate the attribution of three qualities of game viz., winning, drawing, and losing team.

References Abdullah MR, Maliki ABHM, Musa RM, Kosni NA, Juahir H, Haque M (2016a) Multi-hierarchical pattern recognition of athlete’s relative performance as a criterion for predicting potential athletes. J Young Pharm 8:463 Abdullah MR, Maliki ABHM, Musa RM, Kosni NA, Juahir H, Haque M (2016b) Multi-hierarchical pattern recognition of athlete’s relative performance as a criterion for predicting potential athletes. J Young Pharm 8

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Bush M (2017) Contemporary factors impacting match performances of elite soccer players: the development and evolution of performance in the english premier league (Doctoral dissertation, University of Sunderland) Csataljay G, O’Donoghue P, Hughes M, Dancs H (2009) Performance indicators that distinguish winning and losing teams in basketball. Int J Perf Anal Sport 9:60–66 Kubayi A, Toriola A (2020) Match performance indicators that discriminated between winning, drawing and losing teams in the 2017 AFCON Soccer Championship. J Hum Kinet 72(1):215– 221 Maszczyk A, Goła´s A, Pietraszewski P, Roczniok R, Zaj˛ac A, Stanula A (2014) Application of neural and regression models in sports results prediction. Proc Soc Behav Sci 117:482–487 McGuigan M, Hughes D (2018) Martin, Performance indicators in club level Gaelic football. Int J Perform Anal Sport 18:780–795. https://doi.org/10.1080/24748668.2018.1517291 Modric T, Versic S, Jelicic M (2022) Monitoring technical performance in the UEFA champions league: differences between successful and unsuccessful teams. Montenegrin J Sports Sci Med 11(2). https://doi.org/10.26773/mjssm.220901 Musa RM, Abdullah MR, Maliki ABHM, Kosni NA, Haque M (2016) The application of principal components analysis to recognize essential physical fitness components among youth development archers of Terengganu, Malaysia. Indian J Sci Technol 9 O’Donoghue P (2013) Sports performance profiling. In: McGarry T, O’Donoghue P, Sampaio J (eds) Routledge handbook of sports performance analysis. Abingdon: Routledge, pp 127–139 Razali MR, Alias N, Maliki A, Musa RM, Kosni LA, Juahir H (2017) Unsupervised pattern recognition of physical fitness related performance parameters among Terengganu youth female field hockey players. Int J Adv Sci Eng Inf Technol 7:100–105 Taha Z, Haque M, Musa RM, Abdullah MR, Maliki ABHM, Alias N, Kosni NA (2017a) Intelligent prediction of suitable physical characteristics toward archery performance using multivariate techniques. J Glob Pharma Technol Taha Z, Haque M, Musa RM, Abdullah MR, Maliki ABHM, Alias N, Kosni NA (2017b) Intelligent prediction of suitable physical characteristics toward archery performance using multivariate techniques. J Glob Pharma Technol

Secondary School Students’ Perceptions of Motivational Climate, Enjoyment Processes, and Mental Well-being in Physical Education Teo Boon Sian, Chin Ngien Siong, and Matheus Chin Yan Yu

Abstract A motivational climate can engage students to enjoy, learn, and improve their well-being in physical education (PE). The objective of the study was to investigate the motivational climate, enjoyment processes, and mental well-being of secondary school students. The participants were 190 secondary school students (98 male, 92 female) aged 15 to 17 (2.19 ± 0.80) in Kuching, Sarawak. The TeacherInitiated Motivational Climate in PE Questionnaire (TIMCPEQ), Physical Education Enjoyment Processes Questionnaire (PEEPQ), and Warwick Edinburgh Mental WellBeing Scale (WEMWBS) were utilized. Descriptive analysis, independent-samples t-test, one-way ANOVA, and two-way ANOVA were conducted with alpha set at 0.05. The independent-samples t-test revealed a significant difference between gender for teacher-initiated performance orientation, p = 0.02. The one-way ANOVA revealed a significant difference between age groups for activity-generated excitement, F(2, 187) = 14.66, p = 0.01. The one-way ANOVA also revealed a significant difference between ethnicities for parental encouragement, F(2, 187) = 3.43, p = 0.04. The between subjects’ ANOVA between gender and age revealed the main effect of age was significant for activity-generated excitement, F(2, 184) = 15.44, p = 0.01, and teacher-generated excitement, F(2, 184) = 3.33, p = 0.04. There was significant interaction between gender × age for parental encouragement, F(2, 184) = 4.34, p = 0.01. The between subject’s ANOVA between gender and ethnicity revealed the main effect of age was significant for parental encouragement, F(2, 184) = 3.50, p = 0.03. The findings revealed that a positive and adaptive motivational climate would enhance better enjoyment, engagement, and well-being in facilitating the long-term sustainability of the students in PE. Keywords Students · Motivational climate · Enjoyment · Well-being T. B. Sian (B) · C. N. Siong Department of Physical Education and Health, Institute of Teacher Education Batu Lintang Campus, Kuching, Sarawak, Malaysia e-mail: [email protected] M. C. Y. Yu SMK Sungai Maong, Kuching, Sarawak, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_16

191

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1 Introduction Physical inactivity has become an alarming issue since it has been identified as the fourth largest risk factor for global mortality, and its prevalence has increased in developing nations (Rajappan et al. 2015). A lack of physical exercise is associated with the development of non-communicable diseases such as cardiovascular disease, stroke, as well as type 2 diabetes (Katzmarzyk et al. 2022). The prevalence of sedentary behaviour was 66% for undergraduate students in Terengganu (Yusoff et al. 2018), while 55% of Malaysian university students were prone to being physically inactive (Bakar et al. 2019). Research indicated that involvement in numerous physical activities was significantly declining among Chinese schoolaged children and adolescents. Most of them did not reach the minimum 60 min of moderate-to-vigorous physical activity (MVPA) daily recommended by the World Health Organization (Chen 2017; Liu et al. 2018; Wang et al. 2017). Internationally, a significant frequency of 80.3% of adolescents aged 13–15 years from 122 countries and 31.1% of adults aged 15 years old or older from 105 countries were reported as being insufficiently physically active, spending less than 60 min per day on MVPA, despite the fact that males were more active as compared to females (Hallal et al. 2012). Therefore, PE teachers play a vital role in promoting physical activity by establishing and cultivating good attitudes towards physical activity among elementary and secondary school students (Wirght et al. 2000). Hence, it is fundamental for future researchers to evaluate the constructs that promote motivation and participation in PE to develop, sustain, and pursue a healthy lifestyle and lifelong physical activity (Taylor and Lonsdale 2010). Motivation is defined as a psychosocial process that drives individuals to act and is essential for personal development (Ryan and Deci 2000). Internal and external motivation factors might affect one’s desire to carry out a determinant task (Vansteenkiste et al. 2019). In the PE context, motivation drives the students to enrol in physical activity and cultivate their behaviour towards PA engagement (Chu and Zhang 2018; Ning et al. 2015). This behaviour was based on the Achievement Goal Theory (AGT), which states that a task-involving (mastery-oriented) and ego-involving (performance-oriented) climate drives individuals’ ability perception (Nicholls 1989). A mastery-oriented climate emphasizes self-improvement, skill development, prioritizing effort, and mistakes as an inherent component of education and task mastery. In contrast, a performance-oriented climate emphasizes normative criteria, competition with others, less effort, the unacceptability of mistakes, and social status (Ames 1992; Castro-Sanchez et al. 2019; Ruiz et al. 2019). Several studies revealed that a mastery climate was favourably associated with adaptive motivational processes (Barkoukis and Hagger 2013) and enjoyment (Liukkonen et al. 2010), while a performance climate is associated with maladaptive consequences. For example, the perception of mastery climate was found to be associated with high perceptions of ability, attitude, and emotions of satisfaction towards the PE lessons (Treasure and Roberts 2001). A perceived mastery-oriented climate among young handball players was positively associated with task-orientated goals, personal

Secondary School Students’ Perceptions of Motivational Climate, …

193

enjoyment, satisfaction, commitment, and interest, whereas a perceived performanceoriented climate among them was associated with ego-orientated goals, feelings of pressure, and lack of enthusiasm (Granero-Gallegos et al. 2017). Furthermore, the motivational climate has been seen to be more influential as compared to individual goals in adopting and stimulating adolescents’ interest in PE classes (Cury et al. 1996). Studies have demonstrated that a mastery-oriented atmosphere on intention may result in beneficial outcomes, such as pupils playing sports, developing selfdirected motivation, and becoming more physically active to participate in strenuous out-of-school physical activity (Barkoukis and Hagger 2013; Jaakkola 2006). Enjoyment in PE has been considered a vital psychosocial factor that is significantly linked to students’ involvement in physical activity during PE lessons (Garcia Bengoechea et al. 2010; Hashim et al. 2008), as participation in school PE was strongly associated with better leisure-time physical activity among adolescents. Previous studies (Ryan and Deci 2007; Yli-Piipari 2011) revealed that intrinsic and extrinsic motivation contributed to positive behavioural consequences, such as higher enjoyment in PE and increased PA levels. A longitudinal analysis reported that PE enjoyment remained constant among boys while it declined among girls aged 9 to 10 years old (Cairney et al. 2012). Furthermore, boys perceived higher enjoyment than girls among grade 9 students in Finnish (Soini 2006). However, boys’ PE enjoyment decreased from 82% in grade 8 to 71% in grade 10, whereas girls’ PE enjoyment declined from 70% in grade 8 to 62% in grade 10, respectively (Booth et al. 1997). Likewise, a steady reduction in PE enjoyment occurred among the Greek children when they transferred to a higher grade (Digelidis and Papaioannou 1999). Therefore, it is fundamental for the schools’ PE educators to adapt their teaching methodologies and pedagogies to create an enjoyable learning environment during PE lessons that can encourage students to be physically active. Regular physical activity can indirectly enhance an individual’s mental well-being by improving mood and sleep quality, reducing stress and anxiety, and having good physical perceptions and self-esteem (Fox 1999). These showed that involvement in PA frequently has beneficial impacts on children and adolescents’ mental health (Biddle and Asare 2011). Transitioning from primary school into a secondary school environment makes students significantly vulnerable to mental health problems like stress, depression, and anxiety as they face numerous challenges like financial difficulties and academic demands (Fawzy and Hamed 2017). Conversely, declines in physical activity among students were strongly associated with adverse outcomes resulting in poor cognitive functioning (Sallis and Owen 1999) and mental health disorders like anxiety, insomnia, irritability, and acute stress (McMahon et al. 2017). Research indicates that due to performance pressure and academic disruption during the COVID-19 pandemic, college students tend to perceive higher psychological stress, which leads to poor mental well-being (Zhai and Du 2020). These findings highlight the importance of adolescents actively engaging in PA to prevent mental health problems and improve mental well-being (Bell et al. 2019). PE educators need to be responsible for effectively creating meaningful PA during PE classes to promote positive mental well-being among the students. Thus, the purpose of the study was

194

T. B. Sian et al.

to evaluate the perceptions of the motivational climate, enjoyment processes, and mental well-being in physical education among secondary school students.

2 Methods 2.1 Participants A total of 190 secondary school students (Forms 3, 4, and 5) participated in the study. The participants are comprised of 98 males (51.6%) and 92 females (48.4%) aged 15 to 17 years old (2.19 ± 0.80). In terms of ethnicity, a higher proportion of participants were Native (48.4%), followed by Malay (36.8%) and Chinese (14.7%). The BMI categories showed that the majority of the participants were in normal BMI (56.8%), followed by underweight (26.8%), overweight (10.0%), and obese (6.3%). Participants’ mean for frequency of exercise per week were 1.71 (SD = 0.86) averaging between 1 and 30 min per session.

2.2 Measures The 12-item Teacher-Initiated Motivational Climate in Physical Education Questionnaire (TIMCPEQ) (Papaioannou 1998) was conducted to evaluate the perceptions of an individual’s motivational climate in PE lessons. The TIMCPEQ comprises 2 subscales with 6 items each, which are Teacher-initiated Mastery Orientation (TIMO) (e.g. “The PE teacher was most satisfied when every pupil learned something new”) and Teacher-initiated Performance Orientation (TIPO) (e.g. “Only the best pupils were praised by the teacher”). The students rated each question on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The TIMCPEQ and two subscales demonstrated acceptable internal consistency with alpha reliability coefficients of 0.74, 0.80, and 0.77, respectively. The 22-item Physical Education Enjoyment Processes Questionnaire (PEEPQ) (Hashim et al. 2008) was utilized in assessing the teaching processes related to enjoyment in PE. The PEEPQ comprises 7 factors, which are PE enjoyment (PEE) (2 items; e.g. “PE is fun”), self-referent competency (SRC) (4 items; e.g. “My sport skills have improved from doing PE”), other-referent competency (ORC) (4 items; e.g. “My classmate don’t do as well as me in PE”), activity-generated excitement (AGE) (5 items; e.g. “I am enthusiastic about PE activities”), teacher-generated excitement (TGE) (3 items; e.g. “I like the way my teacher explain PE activities to me”), peer interaction (PI) (2 items; e.g. “PE gives me a chance to socialize with my classmates”), and parental encouragement (PE) (2 items; e.g. “My parents encourage my involvement in PE”). Students rated each question on a 5-point Likert scale ranging from 1

Secondary School Students’ Perceptions of Motivational Climate, …

195

(strongly disagree) to 5 (strongly agree). The PEEPQ and seven subscales demonstrated acceptable to excellent internal consistency with alpha reliability coefficients of 0.93, 0.82, 0.83, 0.76, 0.79, 0.77, 0.77, and 0.67, respectively. Whereas, the 14-item Warwick Edinburgh Mental Well-Being Scale (WEMWBS) (Tennant et al. 2007) was conducted to assess the mental well-being among students towards physical activity. The WEMWBS comprises 2 subscales, which are eudaimonic (10 items; e.g. “I’ve been feeling confident”) and hedonic (4 items; e.g. “I’ve been feeling cheerful”). The students rated each question on a 5-point Likert scale ranging from 1 (None of the time) to 5 (All of the time). The WEMWBS and two subscales showed high internal consistency with alpha reliability coefficients of 0.93, 0.89, and 0.81 respectively.

2.3 Procedures The data were collected using Google Form. This study obtained ethnics approval from the Institute of Teacher Education Batu Lintang Campus. Consent was obtained from all participants after they were informed of the purpose, anonymity, and confidentiality of the study.

2.4 Statistical Analysis The data were analysed using the SPSS Statistical for Windows, Version 28.0 (Corp 2021). The gender, age groups, and ethnicity of the TIMCPEQ, PEEPQ, and WEMWBS constructs were investigated using descriptive analysis, independentsamples t-test, one-way ANOVA, and two-way ANOVA.

3 Results Table 1 shows the demographic characteristics of the participants. A total of 190 participants were involved in the study, comprising of 98 males and 92 females. The age groups categories showed that 45 of the participants aged 15 years old, 63 aged 16 years old, and 82 aged 17 years old. In terms of ethnicity, Native formed the largest percentage with 48.4%, followed by Malay and Chinese which comprised 36.8 and 14.7% of the population, respectively. Based on the body mass index, the majority of the participants were in normal weight category with a total of 108, followed by underweight category with 51, overweight category with 19, and obese category with 12. Table 2 shows the mean, standard deviation, and reliability of TIMCPEQ, PEEPQ, and WEMWBS. For TIMCPEQ, teacher-initiated mastery orientation was

196 Table 1 Demographic characteristics of the 190 participants

T. B. Sian et al. Characteristics Frequency (F) Percentage (%) M (SD) Gender

1.48 (0.50)

Male

98

51.6

Female

92

48.4

15

45

23.7

16

63

33.3

17

82

43.2

Age Groups

2.19 (0.80)

Ethnicity

2.60 (1.40)

Malay

70

36.8

Chinese

28

14.7

Native

92

48.4

Normal (18.50–24.99)

108

56.8

Underweight (≤18.49)

51

26.8

Overweight (25.00–29.99)

19

10.0

Obese (30.00–34.99)

12

6.3

BMI

1.96 (0.79)

Times doing exercise (week)

1.71 (0.86)

1–2 times

96

50.5

3–4 times

63

33.3

5–6 times

21

11.1

7 times

10

5.3

Exercise per session (Average)

1.59 (0.80)

1–30 min

109

57.4

31–60 min

54

28.4

61–90 min

22

11.6

91–120 min

5

2.6

the most essential factor that influenced the achievement emotions experienced by trainee teachers, followed by teacher-initiated performance orientation. The overall TIMCPEQ showed acceptable internal consistency of 0.74 while subscales alpha coefficients for teacher-initiated mastery orientation and teacher-initiated performance orientation demonstrated acceptable reliability of 0.80, and 0.77, respectively. For PEEPQ, peer interaction is the most vital factor influencing the students’ enjoyment of physical activity, followed by PE enjoyment, teacher-generated excitement, parental encouragement, self-referent competency, activity-generated excitement,

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and other-referent competency. The overall PEEPQ and seven subscales demonstrated high reliability which ranged from 0.67 to 0.93. For WEMWBS, eudaimonic was the most crucial construct that influenced the trainee teachers’ mental well-being, followed by hedonic. The overall WEMWBS revealed excellent internal consistency of 0.93, while subscales alpha coefficients for eudaimonic and hedonic demonstrated good reliability of 0.89, and 0.81, respectively. Table 3 shows the independent-samples t-test of TIMCPEQ, PE enjoyment, and WEMWBS based on gender. For TIMCPEQ, the results revealed no statistically significant difference between gender for teacher-initiated mastery orientation scores, p = 0.79, but teacher-initiated performance orientation scores, p = 0.02. For PEEPQ, the results also showed no significant difference between gender for PE enjoyment, self-referent competency, other-referent competency, activity-generated excitement, teacher-generated excitement, peer interaction, and parental encouragement with p > 0.05, respectively. For WEMWBS, the results revealed no significant difference between gender for eudaimonic and hedonic with p > 0.05. Table 4 shows the one-way ANOVA of TIMCPEQ, PEEPQ, and WEMWBS based on age groups. For TIMCPEQ, the results revealed that there was no statistically Table 2 Mean, standard deviation, and reliability for TIMCPEQ, PEEPQ, and WEMWBS

Variables

α

M

SD

TIMO

3.97

0.67

0.80

TIPO

2.84

0.72

0.77

PEE

4.09

0.88

0.82

SRC

3.59

0.72

0.83

ORC

2.91

0.78

0.76

AGE

3.52

0.64

0.79

TGE

3.70

0.70

0.77

PI

4.11

0.80

0.77

PE

3.62

0.86

0.67

TIMCPEQ

0.74

PEEPQ

0.93

WEMWBS

0.93

Eudaimonic

3.51

0.74

0.89

Hedonic

3.51

0.86

0.81

Note M = Mean, SD = Standard deviation, α = alpha value, TIMCPEQ = Teacher-Initiated Motivational Climate in Physical Education Questionnaire, TIMO = Teacher-Initiated Mastery Orientation, TIPO = Teacher-Initiated Performance Orientation, PEEPQ = Physical Education Enjoyment Processes Questionnaire, PEE = PE enjoyment, SRC = Self-referent competency, ORC = Other-referent competency, AGE = Activity-generated excitement, TGE = Teacher-generated excitement. PI = Peer interaction, PE = Parental encouragement, WEMWBS = Warwick Edinburgh Mental Well-Being Scale.

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Table 3 Independent-samples t-test of TIMCPEQ, PE enjoyment, and WEMWBS based on gender Variables

Male

Female

t-test

M

SD

M

SD

t

p

TIMO

3.96

0.66

3.98

0.68

− 0.27

TIPO

2.95

0.68

2.71

0.75

2.36

0.02*

PEE

4.10

0.88

4.08

0.87

0.20

0.84

SRC

3.66

0.72

3.50

0.72

1.54

0.13

ORC

2.97

0.67

2.84

0.89

1.18

0.24

AGE

3.57

0.66

3.46

0.62

1.09

0.28

TGE

3.70

0.73

3.70

0.66

− 0.06

0.96

PI

4.14

0.81

4.09

0.79

0.44

0.66

PE

3.68

0.87

3.56

0.86

0.99

0.33

Eudaimonic

3.57

0.78

3.44

0.69

1.24

0.22

Hedonic

3.57

0.88

3.45

0.85

0.98

0.33

TIMCPEQ 0.79

PEEPQ

WEMWBS

∗

p < 0.05

significant difference between the three age groups for teacher-initiated mastery orientation, and teacher-initiated performance orientation with p > 0.05. For PEEPQ, results revealed that there was no statistically significant difference between the three age groups for PE enjoyment, self-referent competency, other-referent competency, teacher-generated excitement, peer interaction, and parental encouragement with p > 0.05. However, there was significant difference between the three age groups for activity-generated excitement, p = 0.01. Post-hoc Tukey adjusted comparisons for activity-generated excitement indicated that the mean score for age group of 15 was significantly lower than age group of 16, µ = 0.38, p = 0.004, and age group of 17, µ = 0.61, p = 0.01. For WEMWBS, the results revealed that there was no statistically significant difference between the three age groups for eudaimonic and hedonic with p > 0.05. Table 5 shows the one-way ANOVA of TIMCPEQ, PEEPQ, and WEMWBS based on age groups. For TIMCPEQ, the results revealed that there was no statistically significant difference between the three age groups for teacher-initiated mastery orientation and teacher-initiated performance orientation with p < 0.05. For PEEPQ, results revealed that there was no statistically significant difference between the three age groups for PE enjoyment, self-referent competency, other-referent competency, activity-generated excitement, teacher-generated excitement, and peer interaction with p < 0.05. However, there was significant difference between the three age groups for parental encouragement, p = 0.04. Post-hoc Tukey adjusted comparisons for parental encouragement indicated that the mean score for Malay was significantly higher than Bumiputera Sarawak, µ = 0.35, p = 0.03. For WEMWBS, the results

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Table 4 One-way ANOVA of TIMCPEQ, PE enjoyment, and WEMWBS based on age groups Variables

Age groups

F

p

15

16

17

TIMO

3.91 (0.63)

3.87 (0.62)

4.07 (0.71)

1.84

0.16

TIPO

2.85 (0.62)

2.68 (0.69)

2.95 (0.79)

2.47

0.09

PEE

3.98 (0.99)

4.21 (0.81)

4.05 (0.86)

1.07

0.35

SRC

3.52 (0.79)

3.52 (0.64)

3.67 (0.74)

1.08

0.34

ORC

2.81 (0.89)

2.84 (0.72)

3.02 (0.77)

1.34

0.26

AGE

3.13 (0.65)

3.51 (0.59)

3.73 (0.59)

14.66

0.01*

TGE

3.53 (0.65)

3.65 (0.67)

3.83 (0.72)

2.91

0.06

PI

3.91 (0.87)

3.20 (0.79)

4.16 (0.76)

1.95

0.15

PE

3.53 (1.02)

3.62 (0.82)

3.68 (0.81)

0.40

0.67

Eudaimonic

3.40 (0.69)

3.54 (0.74)

3.54 (0.76)

0.66

0.52

Hedonic

3.41 (0.88)

3.49 (0.85)

3.59 (0.87)

0.64

0.53

TIMCPEQ

PEEPQ

WEMWBS

∗

p < 0.05

revealed that there was no statistically significant difference between the three age groups for eudaimonic and hedonic with p < 0.05. Table 6 shows the two-way ANOVA for TIMCPEQ, PEEPQ, and WEMWBS based on gender and age groups. For TIMCPEQ, the between-subjects ANOVA for teacher-initiated mastery orientation revealed that there was no significant main effect of gender, p = 0.67, and age groups, p = 0.14. Besides, there was no significant interaction between Gender × Age on teacher-initiated mastery orientation, p = 0.77. The between-subjects ANOVA for teacher-initiated performance orientation revealed that there was significant main effect of gender, p = 0.07, and age groups, p = 0.13. Moreover, there was no significant interaction between Gender × Age on teacher-initiated performance orientation, p = 0.24. For PEEPQ, the between-subjects ANOVA for PE enjoyment revealed that there was no significant main effect of gender, p = 0.97, and age groups, p = 0.32. Besides, there was no significant interaction between Gender × Age on PE enjoyment, p = 0.21. The between-subjects ANOVA for selfreferent competency revealed that there was no significant main effect of gender, p = 0.17, and age groups, p = 0.37. There was no significant interaction between Gender × Age on self-referent competency, p = 0.48. The between-subjects ANOVA for other-referent competency revealed that there was no significant main effect of gender, p = 0.34, and age groups, p = 0.28. Furthermore, there was no significant interaction between Gender × Age on other-referent competency, p = 0.50. The between-subjects ANOVA for activity-generated excitement revealed that there was no significant main effect of gender, p = 0.70, whereas significant main effect of age group, p = 0.01. Moreover, there was no significant interaction between Gender

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Table 5 One-way ANOVA of TIMCPEQ, PE enjoyment, and WEMWBS based on ethnicity Variables

Ethnicity

F

p

4.04 (0.72)

1.98

0.14

2.85 (0.78)

0.96

0.38

4.13 (0.75)

3.96 (0.92)

2.10

0.13

3.45 (0.79)

3.52 (0.73)

2.62

0.08

3.01 (0.64)

3.01 (0.94)

2.80 (0.83)

1.78

0.17

3.59 (0.54)

3.52 (0.64)

3.45 (0.72)

0.94

0.38

TGE

3.78 (0.70)

3.61 (0.62)

3.67 (0.72)

0.82

0.44

PI

4.11 (0.73)

4.05 (0.72)

4.14 (0.88)

0.12

0.89

PE

3.82 (0.70)

3.64 (0.72)

3.47 (0.99)

3.43

0.04*

Eudaimonic

3.54 (0.76)

3.54 (0.64)

3.48 (0.75)

0.16

0.85

Hedonic

3.49 (0.80)

3.57 (0.63)

3.52 (0.91)

0.09

0.91

Malay

Chinese

Native

TIMO

3.96 (0.60)

3.76 (0.61)

TIPO

2.76 (0.67)

2.98 (0.67)

PEE

4.24 (0.84)

SRC

3.74 (0.67)

ORC AGE

TIMCPEQ

PEEPQ

WEMWBS

∗

p < 0.05

× Age on activity-generated excitement, p = 0.06. Post-hoc Bonferroni adjusted comparisons for activity-generated excitement indicated that age group of 15 rated 0.39 point lower than age group of 16, p = 0.01, and rated 0.62 point lower than age group of 17, p = 0.01. The between-subjects ANOVA for teacher-generated excitement revealed that there was no significant main effect of gender, p = 0.66, but significant main effect of age groups, p = 0.04. In addition, there was significant interaction between Gender × Age on teacher-generated excitement, p = 0.23. Post-hoc Bonferroni adjusted comparisons for teacher-generated excitement indicated that age group of 15 rated 0.32 point lower than age group of 17, p = 0.01. The between-subjects ANOVA for peer interaction revealed that there was no significant main effect of gender, p = 0.95, and age groups, p = 0.13. Besides, there was no significant interaction between Gender × Age on peer interaction, p = 0.62. The between-subjects ANOVA for parental encouragement revealed that there was no significant main effect of gender, p = 0.68, and age groups, p = 0.56. Conversely, there was significant interaction between Gender × Age on parental encouragement, p = 0.01. Post-hoc Bonferroni also adjusted comparisons for parental encouragement indicated that male aged 15 years old rated 0.61 point lower than male aged 16 years old, p = 0.01, and rated 0.46 point lower than male aged 17 years old, p = 0.05. For WEMWBS, the between-subjects ANOVA for eudaimonic revealed that there was no significant main effect of gender, p = 0.25, and age groups, p = 0.51. Likewise, there was no significant interaction between Gender × Age on eudaimonic, p = 0.06. The between-subjects ANOVA for hedonic revealed that there was

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no significant main effect of gender, p = 0.51, and age groups, p = 0.47. Similarly, there was no significant interaction between Gender × Age on hedonic, p = 0.10. Table 7 shows the two-way ANOVA for TIMCPEQ, PEEPQ, and WEMWBS based on gender and ethnicity. For TIMCPEQ, the between-subjects ANOVA for teacherinitiated mastery orientation revealed that there was no significant main effect of gender, p = 0.61, and ethnicity, p = 0.15. Besides, there was no significant interaction between Gender × Ethnicity on teacher-initiated mastery orientation, p = 0.60. The between-subjects ANOVA for teacher-initiated performance orientation revealed that there was no significant main effect of gender, p = 0.18, and ethnicity, p = 0.38. Moreover, there was no significant interaction between Gender × Ethnicity on teacher-initiated performance orientation, p = 0.28. For PEEPQ, the betweensubjects ANOVA for PE enjoyment revealed that there was no significant main effect of gender, p = 0.63, and ethnicity, p = 0.13. Furthermore, there was no significant interaction between Gender × Ethnicity on PE enjoyment, p = 0.80, ηp 2 = 0.002. Post-hoc Bonferroni adjusted comparisons for PE enjoyment indicated that Malay rated 0.28 point higher than the Native, p = 0.05. The between-subjects ANOVA for self-referent competency revealed that there was no significant main effect of gender, p = 0.07, and ethnicity, p = 0.06. Besides, there was no significant interaction between Gender × Ethnicity on self-referent competency, p = 0.20. Post-hoc Bonferroni adjusted comparisons for self-referent competency indicated that Malay rated 0.32 point higher than the Chinese, p = 0.04. The between-subjects ANOVA for otherreferent competency revealed that there was no significant main effect of gender, p = 0.09, and ethnicity, p = 0.18. Furthermore, there was no significant interaction between Gender × Ethnicity on other-referent competency, p = 0.33. The betweensubjects ANOVA for activity-generated excitement revealed that there was no significant main effect of gender, p = 0.17, and ethnicity, p = 0.38. Moreover, there was no significant interaction between Gender × Ethnicity on activity-generated excitement, p = 0.69. The between-subjects ANOVA for teacher-generated excitement revealed that there was no significant main effect of gender, p = 0.89, and ethnicity, p = 0.44. Additionally, there was no significant interaction between Gender × Ethnicity on teacher-generated excitement, p = 0.94. The between-subjects ANOVA for peer interaction revealed that there was no significant main effect of gender, p = 0.64, and ethnicity, p = 0.89. Besides, there was no significant interaction between Gender × Ethnicity on peer interaction, p = 0.98. The between-subjects ANOVA for parental encouragement revealed that there was no significant main effect of gender, p = 0.25, whereas significant main effect of ethnicity, p = 0.03. Besides, there was no significant interaction between Gender × Ethnicity on parental encouragement, p = 0.86. Post-hoc Bonferroni adjusted comparisons for parental encouragement indicated that Malay rated 0.36 point higher than the Native, p = 0.01, 95% CI [0.09, 0.63]. For WEMWBS, the between-subjects ANOVA for eudaimonic revealed that there was no significant main effect of gender, p = 0.14, and ethnicity, p = 0.86. Likewise, there was no significant interaction between Gender × Ethnicity on eudaimonic, p = 0.13. The between-subjects ANOVA for hedonic revealed that there was no significant main effect of gender, p = 0.29, and ethnicity, p = 0.93. Similarly,

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Table 6 Main effect of gender and age group for TICMPEQ, PEEPQ, and WEMWBS Variables

SS

df

MS

F

p

TIMCPEQ TIMO Gender

0.08

1

0.08

0.18

0.67

Age

1.76

2

0.88

1.98

0.14

Gender × Age

0.24

2

0.12

0.27

0.77

Gender

1.66

1

1.66

3.29

0.07

Age

2.10

2

1.05

2.08

0.13

Gender × Age

1.44

2

0.50

1.43

0.24

Gender

0.01

1

0.01

0.01

0.97

Age

1.75

2

0.87

1.14

0.32

Gender × Age

2.39

2

1.19

1.56

0.21

Gender

0.99

1

0.99

1.92

0.17

Age

1.05

2

0.52

1.01

0.37

Gender × Age

0.76

2

0.38

0.74

0.48

Gender

0.57

1

0.57

0.93

0.34

Age

1.60

2

0.80

1.30

0.28

Gender × Age

0.86

2

0.43

0.70

0.50

TIPO

PEEPQ PEE

SRC

ORC

AGE Gender

0.06

1

0.06

0.15

0.70

11.03

2

5.51

15.44

0.01∗

2.11

2

1.05

2.95

0.06

Gender

0.09

1

0.09

0.20

0.66

Age

3.17

2

1.59

3.33

0.04∗

Gender × Age

1.41

2

0.70

1.48

0.23

Gender

0.01

1

0.01

0.01

0.95

Age

2.61

2

1.30

2.04

0.13

Gender × Age

0.61

2

0.30

0.47

0.62

0.13

1

0.13

0.18

0.68

Age Gender × Age TGE

PI

PE Gender

(continued)

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Table 6 (continued) Variables

df

MS

Age

SS 0.84

2

0.42

F 0.58

p 0.56

Gender × Age

6.31

2

3.16

4.34

0.01∗

Gender

0.72

1

0.72

1.34

0.25

Age

0.73

2

0.37

0.68

0.51

Gender × Age

3.02

2

1.51

2.82

0.06

Gender

0.33

1

0.33

0.44

0.51

Age

1.11

2

0.56

0.75

0.47

Gender × Age

3.52

2

1.76

2.38

0.10

WEMWBS Eudaimonic

Hedonic

∗

p < 0.05

there was no significant interaction between Gender × Ethnicity on hedonic, p = 0.11.

4 Discussion The study aimed to examine secondary school students’ perception of the motivational climate, enjoyment processes, and mental well-being in Physical Education. The findings showed significant differences in terms of gender, whereby males had higher teacher-initiated performance orientation scores as compared to females. These could be due to the PE teachers attributing unequal instructional approaches between genders in PE sessions from the start. Besides, this showed that males were more extrinsically motivated than females, which revealed that male emphasis on normative feedback, competition, and social comparison. Previous studies indicated that performance orientation was frequently linked to comparison performance and negative dispositions such as pupils might lead to cheating in an attempt to surpass others (Morgan et al. 2006). Moreover, lower levels of students’ mastery goals in PE were significantly associated with the adoption of performance-oriented instructional approaches (Anderman and Young 1994). This revealed that emphasizing performance-oriented climate tends to show the students’ ability differences, whereas emphasizing mastery-oriented climate tends to develop students’ achievement values (Anderman et al. 2001). Hence, students develop a value of performance-oriented climate when learning in evaluative and comparison settings, while mastery-oriented climate develops a value for learning goals (Wigfield and Eccles 1992). Most of the current research believed that those goal orientations, conceived as instructional practices among teachers, were orthogonal with students’ mastery and performance

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Table 7 Main effect of gender and ethnicity for TICMPEQ, PEEPQ, and WEMWBS Variables

SS

df

MS

F

p

Gender

0.12

1

0.12

0.26

0.61

Ethnicity

1.68

2

0.84

1.89

0.15

Gender × Ethnicity

0.45

2

0.23

0.51

0.60

Gender

0.92

1

0.92

1.80

0.18

Ethnicity

1.00

2

0.50

0.97

0.38

Gender × Ethnicity

1.33

2

0.66

1.30

0.28

Gender

0.18

1

0.18

0.24

0.63

Ethnicity

3.15

2

1.58

2.05

0.13

Gender × Ethnicity

0.35

2

0.17

0.23

0.80

Gender

1.73

1

1.73

3.42

0.07

Ethnicity

2.87

2

1.44

2.85

0.06

Gender × Ethnicity

1.64

2

0.82

1.63

0.20

Gender

1.78

1

1.78

2.93

0.09

Ethnicity

2.12

2

1.06

1.74

0.18

Gender × Ethnicity

1.37

2

0.68

1.12

0.33

Gender

0.78

1

0.78

1.86

0.17

Ethnicity

0.81

2

0.41

0.97

0.38

Gender × Ethnicity

0.31

2

0.16

0.37

0.69

Gender

0.01

1

0.01

0.02

0.89

Ethnicity

0.81

2

0.41

0.82

0.44

Gender × Ethnicity

0.06

2

0.03

0.06

0.94

Gender

0.14

1

0.14

0.22

0.64

Ethnicity

0.16

2

0.08

0.12

0.89

Gender × Ethnicity

0.02

2

0.01

0.02

0.98

0.96

1

0.96

1.31

0.25

TIMCPEQ TIMO

TIPO

PEEPQ PEE

SRC

ORC

AGE

TGE

PI

PE Gender

(continued)

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Table 7 (continued) Variables

SS

df

MS

F

p

Ethnicity

5.15

2

2.57

3.50

0.03∗

Gender × Ethnicity

0.23

2

0.11

0.15

0.86

Gender

1.17

1

1.17

2.15

0.14

Ethnicity

0.17

2

0.08

0.15

0.86

Gender × Ethnicity

2.27

2

1.13

2.09

0.13

Gender

0.83

1

0.83

1.11

0.29

Ethnicity

0.10

2

0.05

0.07

0.93

Gender × Ethnicity

3.37

2

1.69

2.27

0.11

WEMWBS Eudaimonic

Hedonic

∗

p < 0.05

orientations (Middleton and Midgley 1997; Nicholls et al. 1990). Thus, PE teachers are recommended to give equal support and guidance to both genders and adopt both mastery and performance motivational climates that can positively affect the psychological needs to cultivate self-determined motivation which has become an imperative task. Furthermore, results also revealed that the older age group perceived higher activity-generated excitement than the younger age group. This result showed that the older age group was more physically active, had a higher level of self-confidence, and enjoyed physical activity compared to the younger age group. The younger adolescents who were physically inactive were susceptible to significant non-communicable diseases and strongly related to being overweight. They adopted a sedentary lifestyle such as spending their time watching television, lying down, and daily sitting time engaging in online activities (Poh et al. 2010). Several studies showed that engaging in PA frequently was significantly associated with greater quality of life, improved mental health, and well-being (Das and Horton 2012; Musich et al. 2017; Schuch et al. 2016). Therefore, regular engagement in PA is fundamental as it helps prevent noncommunicable diseases such as coronary heart disease, stroke, high blood pressure, and diabetes, as well as hypertension and obesity (Rahman et al. 2016). However, older students’ PA enjoyment slightly declined, whereby the percentage of male pupils who enjoyed PE decreased from 82 to 71%. In comparison, female pupils’ enjoyment of PE decreased from 70 to 62% in grade 8 to grade 10 among Australian students (Booth et al. 1997). A constant reduction in PE enjoyment was observed as pupils advanced through the grade levels (Digelidis and Papaioannou 1999). Therefore, PE teachers in schools should emphasize the enjoyment processes that can encourage more satisfaction and excitement for PE and boost students’ participation in meaningful PA.

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Apart from that, results also revealed that the Malay perceived higher parental encouragement than other races. Malay parents tend to emphasize their children’s physical activity more and commit significant time and energy to participate in sports. In contrast, Chinese parents place a greater emphasis on their children’s scholastic accomplishments and psychological control than their Western counterparts (Cheung and Pomerantz 2011). Furthermore, previous studies also indicated that parental supervision and participation may be viewed by Chinese adolescents as a sign of love and concern (Cheung and McBride-Chang 2008). These findings showed that the main motivators of children engaged in physical exercise were their parents because it is strongly related to developing positive attitudes and behaviours towards adolescents (Beets et al. 2010). Previous research found that children with PA interested parents were more socially and emotionally mature and did better in school during PE sessions (Bryce et al. 2019; Lara and Saracostti 2019). The current analysis emphasizes how crucial it is to comprehend parent–child dynamics in terms of educational outcomes that can promote academic success (Savage et al. 2009). As a result, parents play an important role in the development of adolescents’ health behaviours by employing various techniques to influence and encourage their children to participate actively in PA (Crosnoe 2001; Robinsopn and Harris 2013). Therefore, it is critical to ascertain parents’ preferred techniques for addressing their children’s participation in PE and have better achievement. The study’s limitation was that the study focused only on the urban students in a number of schools using a cross-sectional method reducing the ability to make causal inferences. Therefore, future studies could consider rural students when examining these developmental changes in physical education. Secondly, the sample size was relatively small, which cannot be representative of the whole population. Future research should expand a larger sample size covering a few regions in Malaysia.

5 Conclusion The study revealed that a teacher-created motivational climate could increase students’ mental well-being by increasing their level of enjoyment. This supported studies which found that the relationship between mastery climate and enjoyment levels were related to higher satisfaction, interest, and engagement in PE (Hohengasser 2014). Though PE teachers can manipulate the structures of the climate, a mastery and self-referenced approach focusing on self-improvement, skill development, and rewarding effort would lead to more enjoyment and well-being for the students. Acknowledgements We would like to extend our appreciation to all participants for their participation in the study.

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Relationship Between Digit Ratio (2D:4D) and Anaerobic-based Physical Fitness Tests in Children Zulkhairi Azam, Zainal Abidin Zainuddin, Fatin Nadhirah Binti Zulkiflee, Nurul Diyana Binti Sanuddin, Norlaila Azura Binti Kosni, and Fatin Aqilah Binti Razak

Abstract According to studies in digit ratio (2D:4D) field, 2D:4D primarily consists of the index and ring finger ratios. The growth of 2D:4D started in the mother’s womb and affected by the number of sexual hormones of testosterone and oestrogen secretion, as low 2D:4D is associated with higher testosterone content. Thus, this leads to greater potential to compete in various sports and physical fitness with basis of testosterone assisting in muscle and human body development. However, findings regarding the relationship between 2D:4D and anaerobic fitness in younger populations can be rare and inconsistent. Thus, the main purpose of this study is to investigate the relationship of low and high 2D:4D towards anaerobic physical fitness. Total 582 children of male and female with age range from 10 to 12 years old participated in this study. In order to compute the ratio, both hands were scanned and measured, and the hand grip strength test and standing broad jump test were chosen as the test battery. The results showed that due to sexual dimorphism, male children shown lower 2D:4D than female children (p < 0.001). There was a significant connection between low and high 2D:4D in RL HGS for both genders (p < 0.001), as well as in SBJ (p < 0.001). It appears that low 2D:4D male and female groups performed significantly better than the high 2D:4D group. In conclusion, low 2D:4D is associated with performance on anaerobic fitness tests. In order to leverage the capabilities of low 2D:4D as a potential signal for classifying young athletes into sports based on their physical fitness domain, future research should include a greater emphasis on comprehensive anaerobic and aerobic-based fitness tests. Keywords Digit ratio · Anaerobic · Prenatal testosterone · Children

Z. Azam (B) · F. N. B. Zulkiflee · N. D. B. Sanuddin · N. A. B. Kosni · F. A. B. Razak Faculty of Sports Science and Recreation, Universiti Teknologi MARA Pahang Branch, Pahang, Malaysia e-mail: [email protected] Z. A. Zainuddin School of Education, Faculty of Social Science and Humanities, Universiti Teknologi Malaysia, Johor, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_17

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1 Introduction The trend of research on digit ratio (2D:4D) is surging over the past few years as researchers implied that digit ratio has the potential to be a reliable bio-marker in various aspects if given the proper thorough researches. Majority of research agreed that the digit ratio is a surrogate for prenatal testosterone. This is due to 2D:4D itself is affected by exposure to hormones such as foetal testosterone and other androgens during the foetal period. In brief, 2D:4D is calculated by dividing the index finger length (2D) of a particular hand by the same ring finger length (4D) (Putz et al. 2004; Tomkinson and Tomkinson 2017). When it comes to research in sports and fitness testing, lower 2D:4D is always considered as the main variable. Low 2D:4D indicates higher prenatal androgen exposure and can be used as an approximation of prenatal exposure. In a study by Voracek and Loibl (2009), prenatal testosterone and oestrogen levels play a role in forming index and ring finger, and that high foetal environmental androgen levels are associated with low 2D:4D. According to Manning et al. (1998, 2004) as one of the pioneer in 2D:4D research, his studies suggested that 2D:4D acts as a bio-marker for prenatal testosterone. It is well documented that testosterone has an organizing impact on muscle improvement in those long-term, structural results at the body. Because of prenatal testosterone exposure, the development and growth of cardiovascular, musculoskeletal, and urogenital systems are all affected. Increased testosterone exposure results in a low 2D:4D, whereas decreased testosterone exposure results in a high 2D:4D (Erkec 2019; Zheng and Cohn 2011). Naturally, 2D:4D is sexually dimorphic, and males have lower 2D:4D than females. Males often have lower 2D:4D than females. This may be due to the prenatal balance of testosterone and oestrogen due to the high levels of androgen receptors in the foetal 4D (Fink et al. 2007; Trivers et al. 2006). Numerous researches were carried out at the affiliation among digit ratio on overall sports performance together with fencing, football, rugby, and athletic events (Kim and Kim 2016), despite the fact that conclusions are regularly on the premise of a small variety of individuals and most effective on men. On sports that depend on high capacity of anaerobic such as rugby (Azam et al. 2019; Bennett et al. 2010), low 2D:4D was significantly related to those elite athletes. However, there’s a dearth of studies on the sturdy connection among children’ 2D:4D and anaerobic based physical fitness. Looking into previous study in Welsh children by Ranson et al. (2015), they found that low 2D:4D is associated with aerobic capacity, speed, and power in males, but not in females. While Eghbali (2016) on his study among Iranian children, he failed to find connection between 2D:4D with physical fitness tests. Paper by Manning and Hill (2009) stated that low 2D:4D initially was significantly correlated with sprinting speed among young children, but later after cross analysis on effect covariances, the strength of relationship on sprinting speed is deemed as weak. Nonetheless, there are also several findings associating 2D:4D on upper body strength (Nanda and Samanta 2017; Shen et al. 2016) and lower body power (Hsu et al. 2018; Ranson et al. 2015). Focusing on the gap created through various past

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findings, there is a potential for 2D:4D to be relate with anaerobic based physical fitness especially on younger population.

2 Methodology 2.1 Subject Selection The subjects for this study were chosen by using purposive sampling method, and the primary inclusion criteria for it is the subjects must be in normal body mass index (BMI) for participation in this study. The body mass index (BMI) norm for males is established at 15.4–21.0 kg/m2 , while the BMI norm for females is set at 15.2–20.9 kg/m2 . The reason in establishing a normal BMI as the inclusion criteria is to lessen the amount of data bias that is introduced while doing those fitness tests. For instance, children who are overweight may have larger palms, and as a result, they may be able to create greater force during a hand grip strength test. However, because of their bodyweight, they also may not be able to leap as far during a standing broad jump test. In the first place, the subjects in this study were each provided with a consent form and asked their parents or legal guardians for permission to take part. Hence, there was a total of 582 children participated, ranging in age from 10 to 12 years old, with 359 male children and 223 female children enrolled. For information, this research project has been given approval to proceed on the data collection process by the university’s research ethics committee.

2.2 Assessment of 2D:4D The 2D:4D examination was performed by using both hands of the subjects (average 2D:4D). Because of the huge number of subjects to be measured, an indirect 2D:4D measuring approach of hand scanning was adopted, since indirect measurement is also able to produce reliable results. Before beginning work on the hand images in MicroDicom viewer, calibration was performed on it to ensure accuracy of the measurement is not affected. In order to verify the reliability and precision of the measurement, the 2D:4D measurement was carried out twice by a single researcher who has previous expertise in carrying out 2D:4D measurement. Before commencing the 2D:4D measurement, the subjects were first given the instruction to clean their hands and take off any jewellery or other items and that would interfere with the results of the hand images or measurements. The subjects should then place both sides of their hands with their palms facing down and avoid applying an excessive amount of force. Their hands need to be in a straight line and completely enclosed within the Canon CanoScan LiDE 120 scanning equipment at all times. After the hands had been scanned, the images of the hands were brought up

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in the software application known as MicroDicom viewer so that the finger lengths could be measured.

2.3 Assessment of Physical Fitness In order to ascertain the subjects’ levels of anaerobic physical fitness, the subjects participate in a series of anaerobic-based fitness tests. Each test is intended to represent the capabilities of a particular body part. Therefore, the hand-grip strength test (HGS) and the standing broad jump (SBJ) test were chosen in order to measure the strength in the upper body as well as the power in the lower body. When it comes to measuring anaerobic capacity, both of these tests are held to the same exacting standards as the gold standard. This is solely due to the fact that in medical and sporting practise, the HGS test and the SBJ test are frequently used, and they are both capable of providing depth as well as a high depth of validity when measuring and interpreting upper body strength and lower body power. Prior before starting the fitness tests, the subjects undergo warm-up and stretching session to ensure they are physically prepared and lower the risk of getting injured during the tests. Explanation and demonstration on those fitness tests were also shown to the subjects. In addition, subjects were given provided the chance to do trials for familiarization of the fitness tests. For each fitness tests, subjects must perform two times and given appropriate rest time.

2.4 Statistical Analysis For this study, priorly analysis starts with checking for any missing data and the distribution of the data. Intercorrelation coefficient (ICC) with two-way mixed-effect model (Model 3) based on single measure (Form 1) was run to determine that reliability of the 2D:4D measurement. ICC results demonstrated that excellent reliability (0.999) for both hands 2D:4D measurement in male and female subjects. Thus, the ICC result is acceptable for further data analysis. Analysis of covariances was also included in order to check whether variable age and BMI has any effect on 2D:4D by conducting Pearson correlation test. Meanwhile, independent sample t-test was used to check for comparison between low and high 2D:4D between genders, and further used to find comparison between low and high 2D:4D subjects through the scores in the fitness tests. Values were as Mean ± SD, and significance level was set at 0.05. IBMM software statistic version 26 was chosen as the main platform to run all of the data analyses.

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3 Results The descriptive demographic profile of children (N = 582), which includes males (N = 359) and females (N = 223) who participated in this study, is given in Table 1. Subjects ranged in age from 10 to 12 years, with 10-year-old (N = 248), 11year-old (N = 292), and 12-year-old (N = 42). Then, based on the average of male and female 2D:4D, 383 participants had a low 2D:4D. For differences between the genders, there were 254 male individuals with low 2D:4D. Meanwhile, there were 129 female participants with low 2D:4D. Table 2 summarizes the descriptive characteristics of children, which includes males (N = 359) and females (N = 223). Right 2D:4D, left 2D:4D, average 2D:4D, right HGS, left HGS, RL-HGS, and SBJ are the variables being defined. Additionally, the table displays the mean and standard deviation for each variable under examination. Males reported lower 2D:4D in all 2D:4D hand categories compared to females. The same pattern can also be seen on both all physical fitness tests as males scored higher than their females’ counterpart.

3.1 Comparison of 2D:4D Between Male and Female Independent samples t-tests were used to compare 2D:4D of males and females. According to the data in Table 3, there was a significant difference in the 2D:4D Table 1 Subjects’ 2D:4D descriptive Gender

Status

N

Male

359

Female

223

38.30

582

100.00

10

248

42.60

11

292

50.20

12

42

7.20

Total Age (years)

Total 2D:4D (male and female)

582

100.00

199

34.20

Low 2D:4D

383

65.80

582

100.00

High 2D:4D

105

29.20

Low 2D:4D

254

70.80

Total 2D:4D (female) Total

61.70

High 2D:4D

Total 2D:4D (male)

(%)

359

100.00

High 2D:4D

94

42.20

Low 2D:4D

129

57.80

223

100.00

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Table 2 Descriptive and physical fitness data Age (years) Weight (kg) Height (cm) BMI (kg/m2 ) Right 2D:4D (mm) Left 2D:4D (mm) Average 2D:4D (mm) RL HGS (kg) SBJ (m)

Gender

N

Min

Max

Mean ± SD

Male

359

10

12

10.68 ± 0.65

Female

223

10

12

10.60 ± 0.54

Male

359

18

71

32.67 ± 7.89

Female

223

21

58

33.36 ± 6.78

Male

359

1.16

1.68

Female

223

1.22

1.62

1.41 ± 0.07

Male

359

10.76

31.93

16.64 ± 2.55

Female

223

11.71

27.97

16.73 ± 2.22

Male

359

0.85

1.06

0.97 ± 0.04

Female

223

0.88

1.07

0.98 ± 0.04

Male

359

0.87

1.07

0.97 ± 0.043

Female

223

0.90

1.07

0.98 ± 0.042

Male

359

0.86

1.05

0.97 ± 0.04

Female

223

0.89

1.06

0.98 ± 0.04

Male

359

12.60

76.90

30.27 ± 0.22

Female

223

12.30

58.30

28.64 ± 0.57

Male

259

0.78

2.46

1.45 ± 0.30

Female

223

0.50

1.95

1.298 ± 0.27

1.39 ± 0.09

Table 3 2D:4D differences between genders Gender

N

Mean ± SD

t

df

p

Male

359

0.97 ± 0.04

− 4.37

580

0.00

Female

223

0.98 ± 0.04

status of both genders, as indicated by the values p < 0.001, t (df = 580) = − 4.37. (2-tailed). Thus, the digit ratio did have statistical relevance in determining the 2D:4D status of males and females.

3.2 Relationship of Age and BMI Towards to Digit Ratio Table 4 shown that there was no significance distributed between age (p = 0.17) and BMI (p = 0.93) towards 2D:4D on male and female participants. Thus, this result showed that the covariances of age and BMI does not affect 2D:4D, thus can provide true meaning of relationship of 2D:4D towards performance in those physical fitness tests.

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Table 4 Effect of covariances on 2D:4D Variables

2D:4D

p-value

2D:4D

Male Age (years) BMI (kg/m2 )

p-value

Female

0.15

0.78

− 0.92

0.17

− 0.08

0.87

− 0.01

0.93

Table 5 Comparisons of 2D:4D on HGS and SBJ Test

Gender

2D:4D

N

Mean ± SD

RL HGS

Male

Low

254

31.56 ± 9.84

High

105

27.16 ± 656

Low

129

32.06 ± 7.18

High

94

23.93 ± 5.20

Low

254

1.49 ± 0.31

High

105

1.33 ± 0.23

Low

129

1.44 ± 0.21

High

94

1.10 ± 0.20

Female SBJ

Male Female

t

df

p

4.21

357

0.00

9.34

221

0.00

4.86

357

0.00

12.19

221

0.00

3.3 Comparison Between Low and High Digit Ratio on Anaerobic Physical Fitness Table 5 indicates that there was a significant difference between the low and high 2D:4D on the RL HGS for male, p < 0.001, t (df = 357) = 4.201 (2-tailed). Additionally, there was a significant difference in the ratio in low to high 2D:4D on SBJ, p < 0.001, t (df = 357) = 4.86 (2-tailed) for male. Then, for females, there was a significant difference in the ratio of low to high digits on RL HGS p < 0.001, t (df = 221) = 9.34. (2-tailed). Similarly, there was a significant difference in low to high 2D:4D on SBJ, p < 0.001, t (df = 221) = 12.19 (2-tailed) for females.

4 Discussion 4.1 Comparison the Status of 2D:4D on Male and Female The purpose of this study is to ascertain the 2D:4D status of male and female children. The independent samples t-test analysis of Table 3 revealed a statistically significant difference in 2D:4D status between genders, as indicated by the result t (df = 580) = − 4.369 (2-tailed) and p value (p < 0.001). Simultaneously, this conclusion establishes the ratio of male to female participants with a low to high 2D:4D.

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Based on the result, 254 out of 359 male subjects had a low digit ratio. Meanwhile, 129 female subjects had a low 2D:4D, while the remaining 94 had a high 2D:4D. In general, it indicates that 2D:4D is a male–female dimorphism, with males having a lower 2D:4D than females (Putz et al. 2004; Zheng and Cohn 2011). In other words, people with a low 2D:4D had a higher prenatal androgen exposure, as measured by testosterone and another androgen. Additionally, it is believed to be a proxy for the foetal testosterone and oestrogen levels in the mother’s womb during a brief developmental window near the end of the first trimester (Manning et al. 1998, 2003). Males, on average, have a lower 2D:4D than females, according to the majority of prior studies. Males generally have a 2D that is shorter than their 4D, whereas females typically have a 2D that is equal to or longer than their 4D, according to Zheng and Cohn (2011). Boys in that study have a higher proportion of lower 2D:4D than females. Similarly, Voracek (2011) in his systematic review reported that males have a lower 2D:4D than females due to sexual dimorphism.

4.2 Effect of Age and BMI on 2D:4D One of the objectives of this study is to determine the effect of covariates (age and BMI) on 2D:4D. There was no link between age and BMI towards the single 2D:4D for male subjects. The p-value for the relationship between age and 2D:4D is (p = 0.776), whereas the p-value for the relationship between BMI and 2D:4D is (p = 0.874). Similarly, there was no significant link between age and BMI in respect to the 2D:4D for female participants, with p-values of (p = 0.173) and (p = 0.926). As a result, covariates (age and BMI) had no effect on the role of 2D:4D in anaerobic-based physical fitness performance. In contrast to Manning and Hill (2009) study, the researcher initially discovered a correlation between 2D:4D and strength but later concluded that digit ratio is an inaccurate and weak predictor of strength. This is because the researcher used a broad age range of 10 to 17 years old as physical and physiological development of children between the ages of 10 and 17 years visibly varies. However, this study concentrated on a limited age group of 10 to 12 years old to prevent bias in the performance of anaerobic-based physical fitness. Additionally, Ranson et al. (2015) discovered a substantial correlation between 2D:4D and age and BMI. The findings of this study indicated that boys had a correlation between their 2D:4D and their overall physical fitness, whereas girls do not. Because only boys in this study had a normal BMI and there was a strong association between BMI and gender, the researcher included girls with an abnormal BMI. Additionally, that study has a vast age span, ranging from 8 to 12 years old which can result in a bias in physical and physiological development, with people with a larger body size having better strength and power than those with a smaller body size. As mentioned by Klimek et al. (2014), increased muscle mass correlates with increased testosterone levels, and increased fat mass correlates with decreased testosterone levels.

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4.3 Comparison Between Low and High 2D:4D on Anaerobic Physical Fitness As demonstrated by the presence research, the purpose of this study is to would investigate the effects of low and high digit ratios on anaerobic-based physical fitness, which was previously used as a surrogate for prenatal in male and subjects. The result of the presence study determined that there was a significant difference between the low and high 2D:4D on RL HGS. Additionally, the pattern was repeated with significant difference found in SBJ. In general, prior research has indicated that the lower 2D:4D, particularly in males, is most likely related to physical fitness as a result of sexual dimorphism. Males have an edge over females in anaerobic-based physical fitness performance due to both groups’ 2D:4D status (Klimek et al. 2014). Most previous studies (Halil et al. 2013; Koziel et al. 2017; Nanda and Samanta 2017; Tomkinson and Tomkinson 2017) reported connection between 2D:4D and physical fitness components especially on handgrip strength, and mostly were found in males population. In addition to that, Fink et al. (2006) demonstrated a correlation between low 2D:4D and increased mean hand-grip strength but much older in Caucasian German and Mizos Indian men. In contrast to related findings, Eghbali (2016) found no significant link between handgrip strength and age in two groups of Iranian boys aged 7–10 and 11–13 years. Peeters et al. (2013) also stated that physical strength was not correlated with prenatal testosterone. Somehow that research was using left hand 2D:4D as main variable for distinguishing relationship of prenatal testosterone on physical fitness. Yet, in review article on athletic ability by Hönekopp and Schuster (2010) stressed that researchers should use both hands 2D:4D for generating much reliable outcomes as they also mentioned that neither right and left hand 2D:4D out predict each other. Not to forget, the factor of hand preference or handedness also has the capability to influence on the possible outcome. Thus, it is safer and much reliable to include both hands 2D:4D as part of main variable in 2D:4D research fields. Nonetheless, referring to much reliable current review by Pasanen et al. (2021) they concluded that due to organizational effects of prenatal testosterone, muscular strength and overall physical fitness was negatively associated with 2D:4D with both male and female showing the same capability. On the other part, it was determined that the 2D:4D measurement for males and females had a statistically significant relationship with lower limb power as measured in the SBJ test. Nonetheless, a prior study discovered a significant association between males with a low 2D:4D and the SBJ test, but not among female subjects (Ranson et al. 2015). Similar with SBJ, through the vertical jump conducted in past findings (Crewther et al. 2022; Lombardo and Otieno 2021), they noticed a negative correlation of 2D:4D with jumping power. In terms of sexual dimorphism in performance characteristics, the researcher discovered that men outperform women in strength and power-related aspects of sport. While the early organizational effects of testosterone and oestrogen may have had an effect on sex differences and individual variations in terms of fitness or sports performance characteristics (Kim and Kim 2016; Pasanen et al. 2021), it

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is still possible that these effects began early in the organizational life cycle and continued to the present day. Finally, latest researches have established a link between low 2D:4D on SBJ and HGS performance in athletes who are more competitive and successful than those whom participated in aerobic fitness-oriented sports (Crewther et al. 2022; Pasanen et al. 2021). In addition, according to existing studies and reviews, 2D:4D seem to have the potential to forecast on association of high performances among young athletes whom compete in sports that rely heavily on anaerobic fitness (Kim and Kim 2016; Lombardo and Otieno 2021; Pasanen et al. 2021).

5 Conclusion From the results, it is shown that the trait of 2D:4D itself is a sexual dimorphic, with males having a much lower 2D:4D counts than females. Higher percentage of lower 2D:4D can be found in males compared to females. This is in align with past studies in 2D:4D that agreed 2D:4D main trait is sexually dimorphism. The inclusion of anaerobic-based fitness tests in this study provides better understanding on the relationship of 2D:4D with anaerobic capability as most studies usually associates 2D:4D with endurance-based fitness tests. It demonstrates that low 2D:4D also have significant effect on anaerobic fitness component, which is seem to suggest on the benefits of the prenatal testosterone organizational pathway in influencing the muscles growth and physiological development. As 2D:4D concept is still being intensely research worldwide and not yet scientifically accepted, however it is recommended that future studies to include much comprehensive physical fitness components as part of research measurement, with focus on targeting younger population.

References Azam Z, Zainuddin ZA, Ibrahim H, Hashim AHM, Baki MH, Noor MSHM (2019) Prenatal testosterone and sporting success among Malaysian rugby athletes. Indian J Public Health Res Dev 10(4):1474–1479. https://doi.org/10.5958/0976-5506.2019.00923.9 Bennett M, Manning JT, Cook CJ, Kilduff LP (2010) Digit ratio (2D:4D) and performance in elite rugby players. J Sports Sci 28(13):1415–1421. https://doi.org/10.1080/02640414.2010.510143 Crewther BT, Pastuszak A, Sadowska D, Górski M, Cook CJ (2022) The digit ratio (2D:4D) and testosterone co-predict vertical jump performance in athletic boys: evidence of organizational and activational effects of testosterone on physical fitness. Physiol Behav 251:113816. https:// doi.org/10.1016/j.physbeh.2022.113816 Eghbali E (2016) The relationship between digit ratio (2D:4D) and physical fitness in boys 7 to 13 years. Phys Act Rev 4:154–162. http://dx.doi.org/10.16926/par.2016.04.19 Erkeç ÖE (2019) Relationships between the 2D:4D digit ratio, waist circumference, hand preferences, weight, height, waist-to- height ratio and BMI in a Turkish population. Int J Morphol 37(4):1299–1304. https://doi.org/10.4067/s0717-95022019000401299

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Fink B, Thanzami V, Seydel H, Manning JT (2006) Digit ratio and hand-grip strength in German and Mizos men: cross-cultural evidence for an organizing effect of prenatal testosterone on strength. Am J Hum Biol 18(6):776–782. https://doi.org/10.1002/ajhb.20549 Fink B, Manning JT, Williams JHG, Podmore-Nappin C (2007) The 2nd to 4th digit ratio and developmental psychopathology in school-aged children. Personality Individ Differ 42(2):369– 379. https://doi.org/10.1016/j.paid.2006.07.018 Halil M, Gurel EI, Kuyumcu ME, Karaismailoglu S, Yesil Y, Ozturk ZA, Yavuz BB, Cankurtaran M, Ariogul S (2013) Digit (2D:4D) ratio is associated with muscle mass (MM) and strength (MS) in older adults: possible effect of in utero androgen exposure. Arch Gerontol Geriatr 56(2):358–363. https://doi.org/10.1016/j.archger.2012.11.003 Hönekopp J, Schuster M (2010) A meta-analysis on 2D:4D and athletic prowess: substantial relationships but neither hand out-predicts the other. Personality Individ Differ 48(1):4–10. https:// doi.org/10.1016/j.paid.2009.08.009 Hsu C-C, Fong T-H, Chang H-M, Su B, Chi C-P, Kan N-W, Hsu M-C (2018) Low second-to-fourth digit ratio has high explosive power? A prepubertal study. J Strength Cond Res 32(7):2091–2095. https://doi.org/10.1519/JSC.0000000000002435 Kim TB, Kim KH (2016) Why is digit ratio correlated to sports performance? J Exerc Rehabil 12(6):515–519. https://doi.org/10.12965/jer.1632862.431 Klimek M, Galbarczyk A, Nenko I, Alvarado LC, Jasienska G (2014) Digit ratio (2D:4D) as an indicator of body size, testosterone concentration and number of children in human males. Ann Hum Biol 41(6):518–523. https://doi.org/10.3109/03014460.2014.902993 Koziel S, Kociuba M, Chakraborty R, Ignasiak Z (2017) Physical fitness and digit ratio (2D:4D) in male students from Wroclaw, Poland. Coll Antropol 41(1):31–37 Lombardo MP, Otieno S (2021) The associations between digit ratio, aerobic fitness, physical skills, and overall physical fitness of elite youth distance runners. Am J Hum Biol 33(1):e23448. https:// doi.org/10.1002/ajhb.23448 Manning JT, Scutt D, Wilson J, Lewis-Jones DI (1998) The ratio of 2nd to 4th digit length: a predictor of sperm numbers and concentrations of testosterone, luteinizing hormone and oestrogen. Hum Reprod 13(11):3000–3004. https://doi.org/10.1093/humrep/13.11.3000 Manning JT, Bundred PE, Newton DJ, Flanagan BF (2003) The second to fourth digit ratio and variation in the androgen receptor gene. Evol Hum Behav 24(6):399–405. https://doi.org/10. 1016/S1090-5138(03)00052-7 Manning JT, Stewart A, Bundred PE, Trivers RL (2004) Sex and ethnic differences in 2nd to 4th digit ratio of children. Early Human Dev 80(2):161–168. https://doi.org/10.1016/j.earlhumdev. 2004.06.004 Manning JT, Hill MR (2009) Digit ratio (2D:4D) and sprinting speed in boys. Am J Hum Biol 21(2):210–213. https://doi.org/10.1002/ajhb.20855 Nanda B, Samanta PP (2017) The second to fourth digit ratio: a measure of hand grip strength? Int J Adv Med 4(5):1250–1254. https://doi.org/10.18203/2349-3933.ijam20173712 Pasanen BE, Tomkinson JM, Dufner TJ, Park CW, Fitzgerald JS, Tomkinson GR (2021) The relationship between digit ratio (2D:4D) and muscular fitness: a systematic review and meta-analysis. Am J Hum Biol 34(3):e23657. https://doi.org/10.1002/ajhb.23657 Peeters MW, Van Aken K, Claessens AL (2013) The left hand second to fourth digit ratio (2D:4D) is not related to any physical fitness component in adolescent girls. PLoS ONE 8(4):e59766. https://doi.org/10.1371/journal.pone.0059766 Putz DA, Gaulin SJC, Sporter RJ, McBurney DH (2004) Sex hormones and finger length: what does 2D:4D indicate? Evol Hum Behav 25(3):182–199. https://doi.org/10.1016/j.evolhumbe hav.2004.03.005 Ranson R, Stratton G, Taylor SR (2015) Digit ratio (2D:4D) and physical fitness (eurofit test battery) in school children. Early Human Dev 91(5):327–331. https://doi.org/10.1016/j.earlhu mdev.2015.03.005

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Sports Fan’s Motivation among Tunku Abdul Rahman University College (TARUC) Students—An Overview Tracy Tan Li Jing and Tan Chee Hian

Abstract This study investigated sports fan motivation of Tunku Abdul Rahman University College students. 386 students were involved in survey questionnaire consisting demographic and Fan Motivational Scale (FMS) to determine differences motives of being a sports fan according to gender, race, age, level of education and number of years of following the sport. Independent t-Test and ANOVA were used and resulted significance differences in the quality of game (t = 3.763, (df = 384), p < 0.05) and entertainment (t = 2.083, (df = 384), p < 0.05) motives between different genders, whereas ANOVA resulted that there was significance differences of quality of game and motive (F = 3.761, (df = 382), p < 0.05); different races., social (F = 3.364, (df = 382), p < 0.05) motive among the different levels of education and quality of game (F = 12.215, (df = 381), p < 0.05) and sport atmosphere for the number of years of following the sport, respectively. However, there was no significant difference in the sport fan motives among the different ages. The favourite sport, team and athlete of TARUC students were badminton, favourite team sport was Manchester United and favourite individual athlete was Lee Chong Wei. Keywords Sports fan · Fan motivation · Motives · PASSPE-SEA-FSR-UiTM

1 Introduction In recent, the Malaysian sports’ scene had been evolving rapidly. The succeed of the Malaysian athletes at the Rio Olympics 2016 for example, the rise of the various national sports’ leagues and also the opportunity to host high profile events over the years had increased the profile of the Malaysian own sports’ industry. Based on the Department of Statistics Malaysia (DOSM), the sports industry had generated a value gross output of RM18.8 billion, and it was one of the main industries that driven the country’s tourism sector (DOSM 2018; Mahidin 2019). T. T. L. Jing · T. C. Hian (B) Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Shah Alam, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_18

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As the sports industry in Malaysia growth, the number of sporting events also increased. The increase of sporting events were beneficial to the local economy, particularly for events that attract fans’ attendance (Roberts et al. 2016). In addition, the increase of reputable national and international level sporting events which organised would increase the exposure for the sport, teams and athletes in the country. The increased in exposure helped to increase fans following. Fans following the sports actually is an important role for teams, athletes and events in creating marketing strategies and securing sponsorship deals. Great marketing strategies could lead to a better revenue as brands were always looking for a good returned on their past investments (Silva and Casas 2017). Therefore, teams, athletes and events that had greater fan engagement were more favourable for brands to support and attracted sponsorship concerned (Pradhan et al. 2020). Various studied that relating to fan’s motivation towards sports consumption and sports spectatorship (Funk et al. 2009; Paek et al. 2021; Popa and Yusof 2011; Popa et al. 2013). Motivation was one of the drivers for fans to follow the sport, teams and athletes (Paek et al. 2021). A simple behaviour such as attending a sporting event could be more complex than it was, and studies showed that there were various individual motives involved (Funk et al. 2009; Paek et al. 2021). Therefore, it was important to understand the motives of sports fans in the way they following their favourite sports, teams or even athletes. Literatures regarding on sports fans’ motivation were widely done in Malaysia. However, most research did not provide enough information for sports marketers to understand the motives behind an individual whom following a sport, team or athlete for the Malaysia sports market (Popa and Yusof 2011; Popa et al. 2013). Moreover, studies showed that Malaysia had a huge fan base for sports such as badminton and football (Sport 2020), and the young adults tended to be more interested in following sports and then eventually became a fan (Sport 2018; Sport 2019). It was useful for sports’ marketers to understand the motives for young adults as they would be the most likely the key target groups in creating marketing strategies. Therefore, this study focused on Sports Fan’s Motivation among Tunku Abdul Rahman University College (TARUC) Students as far as an overview was concerned.

2 Purpose of Study There were several objectives constructed to be answered liked: • To determine the favourite sport, team and athlete of college students. • To identify the motives of being a sport fan between the different gender of college students. • To identify the motives of being a sport fan among the different ages of college students. • To identify the motives of being a sport fan among the different races of college students.

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• To identify the motives of being a sport fan among the different level of education of college students. • To identify the sports fan motivation with the number of years of following the sport.

3 Significance of Study These study findings would be considered as contributed to several perspectives: Sports industry perspective, especially the growth of youth sports’ markets particularly in Malaysia. In recent years, the rise of social media influence had seen an increased in youth consumers for sports products and events. They were also most likely to be a fan of a sport, team or athlete due to this influence. This would benefit sport’s event organisers, sponsors, sports’ product companies, sports’ marketers, media, sports’ teams, athletes and the development of the particular sport. Socio-psychological perspective, because motives of being a sport fan among private college students would be interesting and helpful to the sports industry. The results enable them to devise new ideas and strategies to promote the sporting events or products to the younger generations or more specifically among private college students. Sports marketers’ perspective, convey the planning process for marketing strategies or ideas to enhance the economic status of the sports, teams or athletes surrounding the youth and the younger generation. It also helped the sports’ marketers to understand the motives or behaviour of a fan when it comes to psychological marketing.

4 Methods It was a quantitative study using the survey method. The questionnaire used for this research was the Sport Fan Motivational Scale developed by Al-Thibiti (2004) with relevance reliability. This study was purposively carried out at Tunku Abdul Rahman University College (TAR UC) Kuala Lumpur (KL) Main Campus. The population at TAR UC KL Main Campus was around 25,000 students. Non-probability sampling was used. Under the non-probability sampling, convenient employed. Therefore, the data collection is from co-curricular students, sport and exercise science students, college team athletes and even volunteers. The sample group was made up of male and female college students between the ages of 18 years old and 25 years old, following at least one sport, team or athlete for at least a year. Participants involved were 386 which accordant to the population of 25,000 as far as Krejcie and Morgan sample size table (1970) was concerned were very cooperative with the researchers’ self-administrated survey.

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5 Findings There were descriptive and inferential statistical used in this study: Descriptive Statistics There was a total of 386 Tunku Abdul Rahman University College students participated in this study. Table 1 outlined the respondents’ profiles. There were male and female respondents that participated. The respondents were grouped into three aged groups: 18–20 years old, 21–23 years old, above 23 years old. The respondents grouped into different education levels as stated: pre-university, certificate, diploma, advance diploma and degree. The respondents were from ethnic groups: Chinese, Malay, Indian and others (Bajau, Kadazan, Thai, Sikh). However, the distribution of demographically was slightly sided to male species, young adults with diploma and Chinese ethnic respondents as far as this private university college situated concerned. Based on Table 1, there were 235 (60.9%) male respondents and 151 (39.1%) female respondents. The majority of the respondents were aged between 18–20 years old with 320 respondents (82.9%), followed by 21–23 years old with 60 (15.5%) and 24–25 years old with 6 (1.6%). Male students with clear ratio of 50% more than females in TARUC and mostly young adults or adolescent ages involved in the feedback of the study. As the result descriptively, 311 (80.6%) of the respondents were diploma students, 44 (11.4%) degree students, 21 (5.4%) in advance diploma students, 7 (1.8%) were Table 1 Démographique Information (N = 386)

Demographic

Group

Frequency

Percentage (%)

Gender

Male

235

60.9

Female

151

39.1

18–20 years old 320

82.9

21–23 years old

60

15.5

Above 23 years old

6

1.6

Pre-university

3

0.8

Certificate

7

1.8

Diploma

311

80.6

Advance diploma

21

5.4

Degree

44

11.4

Chinese

353

91.5

Indian

16

4.1

Malay

13

3.4

Others

4

1.0

Age

Level of education

Race

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certificate students and 3 (0.8%) were pre-university students. In other word, diploma students highly supported local sports events concerned. Based on the Table 1, Chinese respondents consisted of 353 (91.5%) of the overall samples, followed by Indians with 16 (4.1%), Malay with 13 (3.4%) and others with 4 of them (1%), these reflected the ownership by major races in TARUC KL. Favourite Sport, Team and Athlete and Number of Years Following the Sport 20 types of sports and 68 different teams and athletes had been identified as far as favourite sports, teams and athletes by all respondents. Besides that, this study also looked into the number of years that the respondents followed the sport, team or athlete. The number of years grouped into four categories: 1 to 3 years, 4 to 6 years, 7 to 10 years and more than 10 years in order to justify the motive of the TARUC fans towards their favourite and supported events as well. Table 2 showed the favourite sport, team or athlete among all TARUC fans, and Table 3 was the number of years that the respondents followed the sport, team or athletes. Table 2 showed that badminton had been identified by 37.3% of the respondents as their favourite sport, followed by, football (22%), basketball (18.1%), tennis (4.1%), martial arts (3.6%) and squash (2.8%). Badminton was the most favoured and attractive to the audience in this study’s finding. Other sports that also considered as favourite sports were the rest: table tennis, volleyball, swimming, athletics, snooker, Formula 1, softball, netball, rugby, cheerleading, bowling, gymnastics, fitness and ultimate frisbee (2% or less). Lee Chong Wei was identified by 50.7% of the respondents as their favourite athlete, followed by Kobe Bryant and Lin Dan with 5.2% respondents, respectively, Nicol David (4.3%), Michael Jordan (3.3%), Michael Phelps (2.8%) and Roger Federer (2.8%). Lee Chong Wei was the idol and “hero” for this majority respondents. The rest were Usain Bolt, Lebron James, Rafael Nadal, Bruce Lee, Novak Djokovic, Jeremy Lin, Joo Se Hyuk, Christiano Ronaldo, Ronaldinho, Serena Williams, Brodie Smith, Anton Abasov, Timo Boll, Eric Leong, Steven Lopez, Robin Van Persie, Judd Trump, Lionel Messi, Peter Gade, Allen Iverson, David Beckham, Lee Yong Dae, Liu Xiang, Ronnie Coleman, Buakau, Maria Sharapova, Kennisasa Bekele, Cho Ah Ra, Micheal Schumacher, Ratchaknok Intanon, Lim Wei Sheng, Kai Greene, Evgenia Kanaeva, Adam Shahir, Kayoom, Kohei Uchimura (2% or lesser), respectively. In term of team events, Manchester United was identified by 23.8% of the respondents as their favourite team, followed by LA Lakers (15.4%), Chelsea (11.2%) and Team Malaysia, Liverpool, Arsenal and Miami Heat with 6.3%, respectively. Manchester United was the most performed team at the moment, and it was highly showed the capabilities team as far as football around the professional arena considered. Other teams listed the following: teams are K-Tigers, Chicago Bulls, Barcelona, Bayern Munich, Team USA, New York Knicks, Real Madrid, Houston Rockets, Team Germany, Team Italy, LA Clippers, Red Bull Racing, Boston Celtics, Vipers, Panthers, Team Japan, Monster, Team China and All Blacks (3% or lesser).

228 Table 2 Favourite sports, teams and athletes identified of this study

T. T. L. Jing and T. C. Hian Group Favourite Sport

Badminton

Percentage

144

37.3

Football

85

22.0

Basketball

70

18.1

Tennis

16

4.1

Martial arts

14

3.6

Squash

11

2.8

Volleyball

7

1.8

Table tennis

6

1.6

Swimming

6

1.6

Athletics

6

1.6

Fitness

4

1.0

Softball

3

0.8

Netball

3

0.8

F1

2

0.5

Cheerleading

2

0.5

Gymnastics

2

0.5

Ultimate Frisbee

2

0.5

Snooker

1

0.3

Rugby

1

0.3

Bowling Favourite athlete

Frequency

1

0.3

107

50.7

Kobe Bryant

11

5.2

Lin Dan

11

5.2

Nicol David

9

4.3

Michael Jordan

7

3.3

Michael Phelps

6

2.8

Roger Federer

5

2.4

Usain Bolt

4

1.9

Lebron James

4

1.9

Rafael Nadal

4

1.9

Bruce Lee

3

1.4

Novak Djokovic

3

1.4

Jeremy Lin

2

0.9

Lee Chong Wei

(continued)

Sports Fan’s Motivation among Tunku Abdul Rahman University … Table 2 (continued)

Group

229 Frequency

Percentage

Joo Se Hyuk

2

0.9

Christiano Ronaldo

2

0.9

Ronaldinho

2

0.9

Serena Williams

2

0.9

Brodie Smith

2

0.9

Anton Abasov

2

0.9

Timo Boll

1

0.5

Eric Leong

1

0.5

Steven Lopez

1

0.5

Robin Van Persie

1

0.5

Judd Trump

1

0.5

Lionel Messi

1

0.5

Peter Gade

1

0.5

Allen Iverson

1

0.5

David Beckham

1

0.5

Lee Yong Dae

1

0.5

Liu Xiang

1

0.5

Ronnie Coleman

1

0.5

Buakau

1

0.5

Maria Sharapova

1

0.5

Kennisasa Bekele

1

0.5

Cho Ah Ra

1

0.5

Micheal Schumacher

1

0.5

Ratchaknok Intanon

1

0.5

Lim Wei Sheng

1

0.5

Kai Greene

1

0.5

Evgenia Kanaeva

1

0.5

Adam Shahir Kayoom

1

0.5 (continued)

230 Table 2 (continued)

T. T. L. Jing and T. C. Hian Group

Frequency Kohei Uchimura

Favourite team

Table 3 Number of years following the sport, team or athlete (n = 386)

Percentage

1

0.5

Manchester United

34

23.8

LA Lakers

22

15.4

Chelsea

16

11.2

Malaysia

9

6.3

Liverpool

9

6.3

Arsenal

9

6.3

Miami Heat

9

6.3

K-Tigers

4

2.8

Chicago Bulls

4

2.8

Barcelona

3

2.1

Bayern Munich

3

2.1

USA

3

2.1

New York Knicks

2

1.4

Real Madrid

2

1.4

Houston Rockets

2

1.4

Germany

2

1.4

Italy

1

0.7

LA Clippers

1

0.7

Red Bull Racing

1

0.7

Boston Celtics

1

0.7

Vipers

1

0.7

Panthers

1

0.7

Japan

1

0.7

Monster

1

0.7

China

1

0.7

All Blacks

1

0.7

Frequency

Percentage (%)

1–3 years

207

53.6

4–6 years

103

26.7

7–10 years

60

15.5

More than 10 years

16

4.1

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Based on Table 3, the majority of the respondents had been following the sport, team or athlete for 1 to 3 years (53.6%). There was 26.7% of the respondents following the sport, team or athlete for 4 to 6 years, followed by 7 to 10 years was 15.5% and those more than 10 years with 4.1% only. In other word, fulfilled the condition of following at least one year and the more or longer years shoed the more loyal or favourite the spots to the particular respondent. Inferential Statistics Ho1: There Were No Significant Differences in the Motives Mean Score Between Gender Table 4 showed the significant differences of the six motives mean scores between the genders. Based on the findings, there were no significant differences found for the social, escape, boredom avoidance and sport atmosphere motives between genders. However, significant there were differences found for the quality of game motive among respondents with t = 3.736, (df = 384), p = < 0.05 and entertainment motive (t = 2.083, (df = 384), p < 0.05) between genders. Furthermore, the mean score for the quality of game and entertainment motives tended to be slightly higher for male respondents’ responses (quality of game = mean score of 15.00; entertainment with mean score = 11.72) compared to female respondents (quality of game as mean of 14.04, entertainment mean = 11.38). Therefore, it could be concluded that quality of game and entertainment motives were ejected their null hypothesis statistically, whereas social, escape, boredom avoidance and sports atmosphere motives were failed to reject the Ho1.

Table 4 Independent T-Test on the six motives mean scores between the different gender (n = 386) Social Quality of game Escape Boredom avoidance Entertainment Sport atmosphere

Mean

SD

t

df

Sig. (2-Tailed)

11.27

1.777

1.748

384

0.081

10.94

1.888

15.00

2.452

3.763

384

0.000

14.04

2.411

18.64

2.968

1.590

384

0.113

18.14

3.137

16.41

2.989

0.406

384

0.685

16.28

3.082

11.72

1.532

2.083

384

0.038

11.38

1.608

7.25

1.247

1.040

384

0.299

7.11

1.377

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Ho2: There Were No Significant Differences in the Motives Mean Score Among The Races Table 5 showed the significant differences of the six motives mean scores among the different races. There were no significant differences for the social motives, escape motives, boredom avoidance motives, entertainment and sport atmosphere motives. However, there was a significant difference in the quality of game motive among the races concerned (F = 3.761 (df = 380), p < 0.05). Therefore, the quality of game motive was rejected Ho2 whereas social, escape, boredom avoidance, entertainment motives were failed to reject Ho2. Ho3: There Was No Significant Difference in the Motives Mean Score Among Age Groups Table 6 showed the significant differences of the six motives mean scores among the different age groups. Ho3 was failed to be rejected. As conclusion, there was no significance differences for all motives involved among the different age groups. It concluded that age of respondents did not show any differences in their motives to be a fan for any sports, teams and athletes at all.

Table 5 ANOVA test on the six motives mean scores among the different races

Table 6 ANOVA test on the six motives mean scores among the different age groups

F

Sig

Social

0.458

0.712

Quality of game

3.761

0.011

Escape

0.985

0.400

Boredom avoidance

1.102

0.348

Entertainment

1.596

0.190

Sport atmosphere

0.864

0.460

F

Sig

Social

2.527

0.081

Quality of game

0.272

0.762

Escape

1.485

0.228

Boredom avoidance

0.409

0.664

Entertainment

0.447

0.640

Sport atmosphere

0.502

0.606

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Ho4: There Were No Significant Differences in the Motives Mean Score Among the Level of Education Table 7 showed the significant differences of the six motives mean scores among the different level of education. There were five different levels of education involved in this study: pre-university, certificate, diploma, advance diploma and degree. Based on Table 7, there were significant differences for social motive only (F = 3.364, (df = 381), p < 0.05) among the different levels of students’ education background but were not others motive comparatively. In other words, level of education showed differences motive in social domain or socialisation process concerned. Ho5: There Were No Significant Differences in the Mean Score Motives for the Number of Years of Following the Sport Table 8 showed the significant differences of the six mean scores motives among the number of years that following the sport. Based on Table 8, there were significant differences in the quality of game motives (F = 12.216, (df = 382), p < 0.05) and sport atmosphere motives (F = 3.389, (df = 382), p < 0.05) among the number of years that respondents’ following the sport but not all the rest motives among them, in showed that more experiences fans were motivated by the quality of games and atmosphere they were involved. Table 7 ANOVA test on the six motives mean scores among the different levels of education

Table 8 ANOVA Test on the six motives mean scores and the number of years following the sport

F

Sig

Social

3.364

0.010

Quality of game

0.252

0.908

Escape

0.826

0.509

Boredom avoidance

0.246

0.912

Entertainment

1.057

0.377

Sport atmosphere

0.231

0.921

F

Sig

Social

0.546

0.651

12.216

0.000

Escape

1.503

0.213

Boredom avoidance

1.579

0.194

Entertainment

1.725

0.161

Sport atmosphere

3.898

0.009

Quality of game

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6 Summary 1. The study found that TARUC college students’ favourite sport was badminton. 2. The study found that college students’ favourite athlete was Lee Chong Wei. 3. The study found that college students’ favourite sports team was Manchester United. 4. The study found that the quality of game and entertainment motives showed significant differences between genders. 5. The study found that the quality of game motive showed a significant difference among the different races. 6. The study found that there were no significant differences for all sport fan motives among the different age groups. 7. The study found that social motive among the different levels of education showed a significant difference.

7 Recommendation Future research regarding sports fan motivation among working individuals could be interesting. By in depth the knowledge about the motivation factors of being a sport fan among the working individuals would help to increase ticket sales, merchandise sale and many more because these individuals have the constant monthly income. In conclusion, sports fan motivation was an important socio-psychological perspective in expanding the sporting industry regardless in Malaysia or abroad. Therefore, this study was a small contribution to the number of available literatures in this area.

8 Contribution of Authors Tracy Tan Li Jing—author that draught and conducting the research, involved in collecting data as well as analysed data. Interpret and write out of the manuscript. Tan Chee Hian—corresponding author and as the director of PASSPE—Asia Chapter that contributed into the concept and ideas of constructing the study, improvising the flow of the thoughts, draught and interpreting of the findings. Acknowledgements In completion of this study, superb relationship with Professors of Pan—Asia Society of Sports and physical Education (PASSPE) FSR—UiTM Chapter as far as the laboratory concerned. Thanks to all participants from TARUC students and all ethical consents gained from all of them. Special thanks to Faculty of Applied Sciences and Computing, TAR University College for awarded us to do this research with an appropriate platform and also to the proof reader of this manuscript concerned.

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Conflict of Interest Both of us agreed upon the thoughts of this findings and the write out to be published without any self-conflict of interest.

References Al-Thibiti Y (2004). A scale development for sport fan motivation. Doctoral dissertation, The Florida State University. ProQuest Information and Learning Company. Retrieved from https://www.proquest.com/openview/abcfe536cbd94305ec6542f3c5cfb18f/1? pq-origsite=gscholar&cbl=18750&diss=y da Silva EC, Las Casas AL (2017) Sport fans as consumers: an approach to sport marketing. Br J Mark Stud 5(4):36–48 Department of Statistic Malaysia (2018) Economic census 2016: tourism statistics. Retrieved from https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat&cat=448&bul_id= VmZsbTU4NDlFcFZRdVF6ZDF3OW4zZz09&menu_id=b0pIV1E3RW40VWRTUkZocEhy Z1pLUT09 Funk DC, Filo K, Beaton AA, Pritchard M (2009) Measuring the motives of sport event attendance: bridging the academic-practitioner divide to understanding behavior. Sport Mark Q 318:126–138 Krejcie RV, Morgan DW (1970) Determining sample size for research activities. Educ Psychol Measur 30:607–610 Mahidin U (2019) The value of gross output in arts, entertainment and recreation services grew by 5.7 per cent in 2017. Retrieved from https://www.dosm.gov.my/v1/index.php?r=column/ cthemeByCat&cat=458&bul_id=bnVsTGJIdHlkS3ZIbXNkNFJKQW4zUT09&menu_id=b0p IV1E3RW40VWRTUkZocEhyZ1pLUT09 Paek B, Morse A, Hutchinson S, Lim CH (2021) Examining the relationship for sport motives, relationship quality, and sport consumption intention. Sport Manage Rev 24(2):322–344. https:// doi.org/10.1016/j.smr.2020.04.003 Popa A, Yusof A (2011) An examination of sport watching behaviours of students at Universiti Putra Malaysia. World Appl Sci J 15(1):78–83 Popa A, Yusof A, Shah PM, Geok SK (2013) Sport spectatorship motives of Malaysian university students. Int J Sport Studies 3(2):199–204 Pradhan D, Malhotra R, Moharana TR (2020) When fan engagement with sports club brands matters in sponsorship: influence of fan–brand personality congruence. J Brand Manage 27(1):77–92. https://doi.org/10.1057/s41262-019-00169-3 Roberts A, Roche N, Jones C, Munday M (2016) What is the value of a premier league football club to a regional economy? Eur Sport Manag Q 16(5):575–591. https://doi.org/10.1080/161 84742.2016.1188840 Sports N (2018) World football report 2018. Retrieved from https://www.nielsen.com/wp-content/ uploads/sites/3/2019/04/world-football-report-2018.pdf Sports N (2019) Game changer: rethinking sports experiences for generation Z. Retrieved from https://www.nielsen.com/wp-content/uploads/sites/3/2019/12/game-changer-gen-z-sports-rep ort-2019.pdf Sports N (2020) Nielsen fan insights expands coverage in Asia, makes fan behaviour data available for 26 markets worldwide. Retrieved from https://nielsensports.com/nielsen-fan-insights-exp ands-coverage-in-asia-makes-fan-behavior-data-available-for-26-markets-worldwide/

Differences of Knee Flexion Angle at Landing Between Dynamic Tasks: Implication Towards ACL Injury Screening in Females Raihana Sharir , Muhammad Adam Mohd Nor Abadi, Mark A. Robinson, Jos Vanrenterghem, and Radin Rafeeuddin Radin Dzulfakar Abstract The main objective of this study is to determine the differences on knee flexion angle at landing between dynamic tasks. Ten participants ranging from 19 to 27 years old participated in this study. The participants performed all dynamic tasks which consist of Bilateral Drop Vertical Jump (BDVJ), Single-Leg Drop Vertical Jump (SLDVJ) and Single-Leg Hop (SLHOP) for three successful trials. The performance was recorded using handphone cameras. The knee flexion angle was determined during the initial contact at landing phase using the Kinovea Software version 0.9.5. Statistical Package for Social Science (SPSS) Statistic Software was used to analyse the results. One-way ANOVA was used to compare the knee flexion angle across all tasks. Results revealed a significant difference for knee flexion angle across all tasks for both right (p = 0.000) and left leg (p = 0.000). In addition, multiple comparison showed that there was significant difference in BDVJ when compared to both SLDVJ and SLHOP for both right and left leg, respectively, (p value < 0.05). However, there was no significant difference on knee flexion angle between SLHOP and SLDVJ on both right (p = 0.989) and left leg (p = 0.971). Differences and similarities in movement patterns between tasks were observed when participants performed bilateral and unilateral movements. This shows that observing single task alone may not disclose more about the individual’s neuromuscular strategies. Keywords ACL · Injury screening · Knee injury · Dynamic tasks

R. Sharir (B) · M. A. M. N. Abadi · R. R. R. Dzulfakar Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Shah Alam, Malaysia e-mail: [email protected] R. Sharir · R. R. R. Dzulfakar Sports and Exercise Biomechanics Special Interest Group, Faculty of Sport Science and Recreation, Universiti Teknologi MARA, Shah Alam, Malaysia R. Sharir · M. A. Robinson School of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK J. Vanrenterghem Faculty of Kinesiology and Rehabilitation Sciences, Leuven, KU, Belgium © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_19

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1 Introduction Non-contact anterior cruciate ligament (ACL) rupture is a common and painful injury that affects athletes in sports like basketball and football (Carbone and Rodeo 2017). In the UK, there were 133,270 cases of ACL reconstruction between the year 1997– 1998 and 2016–2017 (Abram et al. 2020). Not only that, the cost of ACL reconstruction surgery is between £4,945 and 8,805 for private hospitals while, for the National Health Service, it’s around ~ £3000–3500 (Sharir 2018). Furthermore, the significant effect of post-ACL reconstruction can be worrying; for instance, Waldén et al. (2016) found that only 65% of the ACL injured football players out of 93 could perform at the same level before their injury after three years of post-surgery. Moreover, ACL injury patients tend to develop post-traumatic osteoarthritis, which is debilitating for younger athletes as it develops throughout time (Carbone and Rodeo 2017). As a result of a previous ACL injury, hundreds of thousands of previously active persons developed symptomatic post-traumatic knee osteoarthritis at a young age, which has a significant negative impact on individual’s quality of life and associated healthcare expenses (Pappas et al. 2017). The non-contact ACL injury typically occurs when the athlete decelerates, sidesteps and landing (Pappas et al. 2017). Hewett et al. (2016) suggested ligament injuries occur in a movement beyond the physiologic range, such as valgus collapse mechanism, which includes multi-planar pressures of tibial abduction, anterior tibial translation and external or internal tibial rotations. It usually results from a single-leg landing manoeuvre performed from various vertical heights, horizontal distances and is frequently executed in most sports such as football, basketball and handball (Ali et al. 2014). Therefore, single-leg landing tasks may place significantly more stress than the bilateral movements, hence, have the potential to distinguish between highand low-risk individuals (Cruz et al. 2013). Stress on the ACL is caused by dynamic and modifiable biomechanics of the knee, such as hyperextension, high knee abduction or abduction moments (Nessler et al. 2017). Findings by Leppänen et al. (2017) indicated that lower knee flexion leads to hyperextension associated with the increased risk of ACL injury. Another study stated that high knee abduction moments, high knee abduction angle and high ground reaction forces correlate with ACL injuries from a jump landing task with 78% sensitivity and 73% specificity (Hewett et al. 2016). Zahradnik et al. (2014) also found that run-back landing in volleyball produces high vertical ground reaction forces associated with the risk of ACL injury. Therefore, these abundance of information from previous findings warrant further study as aforementioned risk factors could predict ACL injury risk in female athletes who has greater fold of suffering this injury than male athletes (Hewett et al. 2016). Previous studies by Sinclair and Bottoms (2019) and Hewett et al. (2016) identified that female athlete have higher risks of attaining ACL injury than their male counterparts based on several biomechanical factors. They perform high-risk athletic movement during sports play with excessive knee valgus, hip adduction, and hip internal rotation, leading to ACL injury (Pappas et al. 2017). Therefore, clinical evaluation methods to identify athletes at-risk of

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injury would enable physicians to focus on the populations that would benefit the most from rehabilitation (Hewett et al. 2016). Several prospective studies have suggested biomechanical risk factors for noncontact ACL injury (Hewett et al. 2005, Krosshaug et al. 2016, Leppänen et al. 2017). Previously, prospective study by Hewett et al. (2005) found that the knee abduction angle at initial contact and peak knee abduction moment by using bilateral drop vertical jumps was associated to non-contact ACL injury. Another prospective study identifying non-contact ACL injury by Leppänen et al. (2017) revealed the peak knee flexion angle as well as peak ground reaction force, also by the bilateral drop vertical jump task only. Astoundingly, none of these studies found the same biomechanical risk factors associating to the non-contact ACL injury. Since the majority of risk factors were observed in three dimensions (3D), the knee flexion angle is the only risk factor that is two dimensions (2D), which is more practicable and easier to observe from a kinematic standpoint. As previous prospective studies only observed this risk factor in one task which does not really reflect the mechanisms of non-contact ACL injury, more studies are needed using multiple dynamic tasks that could perhaps mimic how the injury occurs. Observing multiple tasks may also determine the consistency of the individual’s movement pattern across those tasks. Moreover, studying individuals over various tasks could determine whether they regularly score at-risk compared to their peers and may disclose more about that individual’s neuromuscular strategies than any other observation made in a single task alone, and these could likely to be hard-wired behaviours that are task-invariant and represent athlete’s at-risk behaviour (Sharir 2018). Therefore, the purpose of this study is to determine the differences on peak knee flexion angle at landing between different dynamic tasks, which are the bilateral drop vertical jump, single-leg drop vertical jump and single-leg hop.

2 Methods Upon ethical approval of the Universiti Teknologi MARA’s Research Ethics Committee, recruitment of female athletes (n = 10) aged between 18 and 35 years old who were free from lower limb injuries within the past 12 months before testing was done. Participants were involved in dynamic sports such as football, basketball, volleyball and netball. Par-Q form, injury history questionnaire and information sheet were given to the participants before the testing.

2.1 Instrumentation Bilateral (BDVJ) and Single-leg (SLDVJ) Drop Vertical Jump Protocols BDVJ and SLDVJ were carried out with a maximum height of 30 cm according to the protocol carried out from previous study (Leppänen et al. 2017). Participants required

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Fig. 1 Bilateral drop vertical jump sequence Permission has been granted to use this image (Sharir 2018)

Fig. 2 Single-leg drop vertical jump sequence Permission has been granted to use this image (Sharir 2018)

to stand on the box with both their feet shoulder width apart before jumping with both legs and land simultaneously for BDVJ (Fig. 1). The SLDVJ required the participants to jump off with one leg and land with the other leg staying off the ground. Upon landing on the ground, the participants instantly performed a maximum vertical jump while raising their arms above the air (Fig. 2). Both right and left legs were measured for SDVJ. Single-Leg Hop (SLHOP) SLHOP task is included to simulate deceleration stopping, which is frequently related to an injury. Participants were instructed to begin on one leg and jump forward to the centre of the platform on that leg while maintaining the other leg off the ground. The length of the hop was determined by measuring the participant’s greater trochanter to the lateral femur length. A successful execution was defined as a firm landing with no movement or wobbling and a single impact on the ground. The SLHOP task was evaluated from both legs.

2.2 Procedures After receiving ethical approval, the information sheet, injury history questionnaire and PAR-Q form were provided to participants to determine their eligibility for the study. Once the participants were recruited, the consent form was given on the testing day to obtain permission before the testing. Prior to testing, participants performed dynamic warm-up which consist of cycling on static bike and dynamic stretching. After 10 min of dynamic warm-up, each participant was randomly assigned to

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perform BDVJ, SLDVJ and SLHOP on both legs. Each task were performed three times and participants were given practice trials to ensure that they were sufficiently familiarized before completing each dynamic task. A 5-min rest in between tasks were given to avoid fatigue.

2.3 Kinematic Assessment of the Dynamic Tasks Motion data of the knee flexion angle at landing were captured from the sagittal plane view using handphone (iPhone Xr) cameras on both right and left side. Reflective spherical markers were attached to the participants on their greater trochanter, lateral femur and lateral malleolus based on the LJMU Lower Limb and Trunk Model (Malfait et al. 2014). Motion data were analysed using Kinovea Software Version 0.9.5 to determine the participant’s knee flexion angle. The outcome measures observed were the knee flexion angle at the landing of the dynamic tasks and knee flexion angle differences across all dynamic tasks.

2.4 Data Analysis Descriptive statistics were used to determine the mean and standard deviation of demographic data (age, height, body weight and BMI). Inferential statistics were determined using Statistical Package for Social Science (SPSS) Statistics 20.0 Software. One-way ANOVA was used to compare the mean value of differences of the knee flexion angle across all dynamic tasks.

3 Results This study determined the differences of knee flexion angle across all dynamic task in female athletes. This study involved (N = 10) (age: 22.20 ± 2.30, height: 155.31 ± 5.72, weight: 53.10 ± 4.72, BMI: 22.13 ± 2.82). An analysis of variance reveals that the knee flexion angle on right leg differences between all dynamic tasks was significant F (2,27) = 13.50, p = 0.000. Multiple comparison was made for the differences on knee flexion angle between Bilateral Drop Vertical Jump (BDVJ), Single-leg Drop Vertical Jump (SLDVJ) and Single-leg Hop (SLHOP) for right leg (Table 1). There was significant difference between BDVJ and SLHOP (p = 0.000) and between BDVJ and SLHOP (p = 0.000). However, no significant difference was observed between SLHOP and SLDVJ (p = 0.989). While for the left leg, analysis of variance shows that the knee flexion angle differences between all dynamic tasks was significant F (2,27) = 21.922, p = 0.000.

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Table 1 Multiple comparison of knee flexion angle across all dynamic tasks (right leg) (I)Task BDVJ SLDVJ

(J)Task

Mean difference (I − J)

Std. error

SLDVJ

−

19.82000*

4.47704

SLHOP

− 20.46000*

4.47704

19.82000*

BDVJ

∗

− 0.64000

95% confidence interval Lower bound

Upper bound

0.000

− 30.9205

− 8.7195

0.000

− 31.5605

− 9.3595

4.47704

0.000

8.7195

30.9205

4.47704

0.989

− 11.7405

10.4605

BDVJ

20.46000*

4.47704

0.000

9.3595

31.5605

SLDVJ

0.64000

4.47704

0.989

− 10.4605

11.7405

SLHOP SLHOP

Sig

The mean difference is significant at the 0.05 level.

Table 2 Multiple comparison of knee flexion angle across all dynamic tasks (left leg) (I)Task

(J)Task

Mean difference (I − J)

Std. error

Sig

Lower bound

Upper bound

BDVJ

SLDVJ

− 22.13000*

3.78562

0.000

− 31.5161

− 12.7439

SLHOP

−

21.26000*

3.78562

0.000

− 30.6461

− 11.8739

22.13000*

3.78562

0.000

12.7439

31.5161

0.87000

3.78562

0.971

− 8.5161

10.2561

21.26000*

3.78562

0.000

11.8739

30.6461

3.78562

0.971

− 10.2561

8.5161

SLDVJ

BDVJ SLHOP

SLHOP

BDVJ SLDVJ

∗

− 0.87000

95% confidence interval

The mean difference is significant at the 0.05 level.

Table 2 shows the significant differences of knee flexion angle between BDVJ, SLDVJ and SLHOP for the left leg. There was significant difference between BDVJ and SLDVJ (p = 0.000) and between BDVJ and SLHOP (p = 0.000). However, no significant difference was seen for SLHOP and SLDVJ (p = 0.971).

4 Discussion This study determined the differences for peak knee flexion angle at initial contact across dynamic tasks among (N = 10) female athletes. All participants performed three dynamic tasks consist of Bilateral Drop Vertical Jump (BDVJ), Single-leg Drop Vertical Jump (SLDVJ) and Single-leg Hop (SLHOP) where the knee flexion angle was observed. Our results show significant differences when comparing all dynamic tasks, respectively, for both right and left leg; however, it indicates no further information of which tasks are different to the other or not. As not much is known from comparing across all tasks, multiple comparison between each dynamic task was made to determine specifically which of the task propose significantly different outcome than

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the other. Based on this study’s Tables 1 and 2, the knee flexion angle observed in BDVJ was significantly different when compared with both SLHOP and SLDVJ for both legs. This finding perhaps indicates that there were differences in terms of movement patterns and neuromuscular strategies when performing different type of movements which was produced by bilateral and unilateral tasks. Another possible reason for these differences could also be that the bilateral tasks could not effectively represent the lower body movements and injury risk that occurs during a singlelegged task (Taylor et al. 2016). With reference to the tasks observed, our outcomes were akin to Harty et al. (2011) and Kristianslund and Krosshaug (2013)’s findings who observed across single-legged and bilateral tasks. As both single-legged tasks (SLDVJ and SLHOP) showed no significant difference for both legs, this further shows that possibly similar movement strategies was used to land these tasks. In contrary to this study’s findings, previous studies comparing risk factors across tasks have also found strong to moderate relationships between single-legged and bilateral tasks in knee angles and moments (Harty et al. 2011). Even though singlelegged and bilateral tasks were very different in terms of physical demands, when observing peak knee abduction angle and peak knee abduction moment; similar dynamic control of lower extremity and knee position across step-down, single leg landing and BDVJ could be seen (Harty et al. 2011). The significant differences seen across tasks might suggest that there is no generic motor pattern across the tasks. This does not necessarily mean however that there is no common underlying muscle synergy across a variety of tasks as the global demands of these tasks are the same. There may well be general synergies, but that are then refined according to the specific task, leading to different biomechanics. An understanding beyond biomechanics such as the influence of the motor control, movement patterns and learning processes, prior to and during task execution, warrants further research. Thus, these findings could suggest that when assessing for biomechanical risk factor of ACL injury, it is best to observe the single-legged tasks side by side to disclose the movement patterns of athletes who probably at risk of getting an ACL injury. Moreover, this type of movements requires high neuromuscular demand compared to the bilateral movements. Observing existing patterns or behaviour (regularities) of the risk factor interactions across tasks could lead to an advancement of risk-profile identification (Bittencourt et al. 2016). Moreover, studying individuals over various tasks could determine whether they regularly score at-risk compared to their peers and may disclose more about that individual’s neuromuscular strategies than any other observation made in a single task alone, and these are possible behaviours that are task-invariant and could signify athlete’s at-risk profiles. Acknowledgements Authors thank the Geran Penyelidikan Penyelidik Muda Berbakat (YTR) by UiTM for the financial support.

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Changes on EEG Power Spectrum with Carbohydrate Mouth Rinsing Harris Kamal Kamaruddin , Al-Hafiz Abu Bakar , Nurul Farha Zainuddin , Mohammad Shahril Salim, and Saidatul Ardeenawatie Awang

Abstract Carbohydrate (CHO) mouth rinse has been shown to activated brain regions via oral receptors that related to rewards and motor control that can enhance exercise performance. The objective of this study was to examine the effect of CHO mouth rinsing on electroencephalography (EEG) power spectrum responses. Ten recreational athletes performed a mouth rinsing for 10 s with CHO or placebo (PLB) solution on seated position, eyes closed and in air conditioning room. The EEG was measured during the initial mouth rinsing with 14 electrodes attached on the participant’s scalp. The EEG activity included alpha, beta, delta, and theta power increased following mouth rinsing (CHO and PLB). However, a significant alpha power was observed with CHO when compared to PLB mouth rinsing on frontal and temporal regions (p = 0.003). No significant differences within beta, delta, and theta power for both solution comparisons, respectively (p > 0.05). The results of this study demonstrate that brain activity may be related to the presence of CHO mouth rinsing. The changes in cortical responses particularly in alpha power may influence the increased of arousal and motivation level. Keywords EEG · Brain activity · Carbohydrate · Mouth rinsing H. K. Kamaruddin (B) · A.-H. A. Bakar · N. F. Zainuddin Faculty of Sports Science and Recreation, Universiti Teknologi MARA Cawangan Perlis, Kampus Arau, Perlis, Malaysia e-mail: [email protected] A.-H. A. Bakar e-mail: [email protected] N. F. Zainuddin e-mail: [email protected] M. S. Salim · S. A. Awang Biomechanics, Signals and Modeling Cluster, Sport Engineering Research Centre (SERC), Universiti Malaysia Perlis, Arau, Perlis, Malaysia e-mail: [email protected] S. A. Awang e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_20

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1 Introduction The presence of CHO in the mouth (via mouth rinsing) has been shown to provide ergogenic benefits during prolonged endurance performance (Bataineh et al. 2018; Kamaruddin et al. 2019). The mechanism of this improvement was due to the presence of CHO in the mouth appearing to activate a novel signaling pathway to the brain region that was associated with motor control, reward, and motivation (Chambers et al. 2009). A functional magnetic resonance imagery (fMRI) study conducted by Chambers et al. (2009) found that the blood oxygenation leveldependent (BOLD) activity increased in several brain regions including insula/frontal operculum, orbitofrontal cortex, and striatum which are associated with improvement in cycling performance. Moreover, the present CHO in the mouth was believed to enhance the neural activation networks within the brain region that are involved in sensory perception (Abu Bakar et al. 2017; Turner et al. 2014). While the fMRI is a technique for measuring and mapping brain activity, the EEG illustrated brain waves activity that reflected affective and perceptual responses (arousal level, concentration, focus, and relaxation) (Morinushi et al. 2000). The changes in the brain waves (alpha, beta, delta, and theta) would enhance understanding of how the brain reacts to different stimuli. With evidence of CHO in the mouth enhancing exercise performance associated with central effect (brain), the brain waves activity remains unknown. Brain activity has been suggested to be important in examining affective and perceptual responses during acute exercise bouts (Petruzzello et al. 2006). Electroencephalography (EEG) currently is the most practical way to monitor human brain activity changes while exercising (Bailey et al. 2008). Brain activity changes can describe the relationship between affective and perceptual responses to exercise (Bailey et al. 2008). The EEG signal contains several spectrum frequencies which are divided into several different frequencies including delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (13–30 Hz), and gamma (>30 Hz) (Devilbiss et al. 2019). A study by Morinushi et al. (2000) investigating the EEG activity changes of chewing flavored gum found an increase in alpha, beta, and theta activity in the frontal region. The authors also found that there were higher changes in similar bands with added flavored gum that could stimulate concentration with a pleasant high arousal state in brain function. The presence of substances in the mouth cause changes in the EEG activity; however, the presence of carbohydrate solution remains unclear. Thus, it can be expected that the presence of carbohydrates CHO in the mouth may increase brain activity and would specifically relate to mood and cognitive function. Therefore, the objective of this study was to examine the effect of CHO mouth rinsing on EEG power spectrum responses. Subsequent paragraphs, however, are indented.

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2 Methods 2.1 Participants Ten recreational male athletes without any history of physical injury or illness were recruited for this study (mean age 23 ± 2 years; height 1.64 ± 0.08 m; body mass 71.6 ± 8.4 kg; and duration sports involvement 4 ± 2 years). All participants were habitually active in regular sports activity (3 ± 1 training per week) and competing in a social sports event. All participants were brief on all measuring protocols and objectives of the study. A pre-experimental was conducted to familiarize participants with the equipment used EEG scanning protocol, and the mouth rinsing technique. All participants were provided a written consent form before participation. This study was approved by Universiti Teknologi MARA Human Ethics Committee (REC/03/2021 UG/MR/153) and conformed to the Declaration of Helsinki.

2.2 Experimental Protocol Participants made a total of three visits to the laboratory. The first visit included the physical assessment (body stature and body mass), familiarization with the scanning equipment, and mouth rinsing protocol. The next two visits were experimental trials where EEG scanning was applied to determine the power spectral of the brain waves with the intervention of mouth rinsing protocol. Each experimental trial consisted of a baseline and three cycles of EEG scanning with mouth rinsing intervention (either CHO or sucralose; PLB). One hour prior to the experiment, participants were given a standardized breakfast that contained 2.5 g.kg−1 (179 ± 21 g) body mass of CHO (cereal, bread, and plain water). The experimental trials were conducted in a seated position, eyes closed, in a controlled temperature room (~22°C), with consistent lighting and less noise room. Participants were informed of the EEG scanning start que and the insertion of water into the mouth. The EEG scanning was recorded once the participant starts rinsing and ended once the solution expectorated into a container. This protocol was repeated for three cycles with 60 s rest between mouth rinsing. All two experimental trials were completed in a counterbalance, randomized, double-blind design and were conducted in the morning (0800–1100 h). Twenty-four hours before each experimental trial, all participants were not allowed to engage in strenuous physical activity, alcohol, or caffeine consumption and were required to sleep at least 6 h. The schematic of the experimental protocol as shown in Fig. 1.

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Fig. 1 Schematic diagram of the experimental protocol

2.3 EEG Data Acquisition, Processing, and Future Extraction The EEG recordings were recorded using EMOTIVE POX + with 14 electrodes (AF3, AF4, F7, F8, F3, FC5, FC6, F4, T7, T8, O1, O2, P7, P8) channel device attached to the participant’s head. The ordinances were followed with an international standard of 10/20 electron location system. Figure 2 depicted the location of the electrodes. A saline injection was inserted to the electrode channel to provide a stable electrode attachment. The EEG recording started according to the experimental protocol when the participant was ready in a relax condition. Participant was requested to minimize body movement to reduce artifacts in the recording signals. The sampling frequency and bandwidth were set at 128 Hz and 0.2 to 45 Hz for EEG signal recording, respectively, with a digital cut-off filter at 50 and 60 Hz. The EEG pre-processing was applied to eliminate the noise signal during the data acquisition. The independent component analysis (ICA) was used to remove unwanted signals. The 4-frequency band, which includes alpha wave (8–13 Hz),

Fig. 2 Diagram of the EEG device and location of the electrode’s location during the EEG test

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low beta wave (13–20 Hz), high beta waves (20–30 Hz), and gamma wave (30– 45 Hz) were extracted using finite impulse response (FIR). The segmentation of the EEG framing signal will be recorded at 1 s in 1 segment (128 sampling data). The future linear analysis was implemented through the power spectral to estimate the EEG signal from a feature vector. Linear feature extraction was applied using power spectral density (PSD) (Ong et al. 2018) Welch and Burge method. Since EEG is nonlinear signal in nature, thus approximate entropy (ApEn) and hurst exponent (HE) method were also applied. Thus, the performance of linear and nonlinear algorithm can be compared. The PSD Welch spectrum measure strength of energy via power signal with frequency. This analysis provides mathematical equation of frequency analysis for a complex waveform. PWelch defines as estimator of spectral density that average the modified periodograms, Pd on the windowed sections from possible overlapped sections (Halim et al. 2021).

2.4 Mouth Rinsing Solution and Procedures The CHO solution consisted of 6% glucose (Sim Company, Penang, Malaysia), while the placebo (PLB) used in this study were artificial sweeteners (sucralose, Diabetasol, Jakarta, Indonesia). All solutions were freshly prepared by an external investigator (not part of this study) before each trial and kept at room temperature. The CHO and PLB solutions were indifferent and matched to the same color and appearance. Both solutions contain sweetness; however, only CHO contains calorie. During the experimental trials, participants received 25 mL of respective mouth rinsing solution to be swirled in the mouth with one tongue movement to distribute the fluid in the mouth for 10 s and expectorated into a container.

2.5 Statistical Analysis All data are presented in mean and standard deviation (mean ± SD) and were analyzed using Statistical Package for Social Science (SPSS version 26.0, Chicago, IL, USA). A pair sample t-test was used to detect any significant difference in brain waves power (alpha, beta, delta, and theta) within the mouth rinsing solutions (CHO and PLB). The level of statistics was set at p < 0.05.

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Fig. 3 Changes in four wave power at frontal region (F3) with CHO and PLB mouth rinsing. *Significant difference between CHO and PLB (p < 0.05)

3 Results The EEC recording showed a surge increase in alpha power at the frontal region (F3) with CHO mouth rinsing solution when compared to PLB. Statistical analysis revealed that there was a significant difference in alpha power for CHO when compared to PLB mouth rinsing (t(9) = 4.121, p = 0.003) (Fig. 3). However, there was no significant difference in beta, delta, and theta power between CHO and PLB, respectively (p > 0.05). A similar finding was also found in the temporal region (T7) with CHO shown an increased in alpha power compared to PLB mouth rinsing. Statistical analysis revealed that there was a significant difference in alpha power for CHO when compared to PLB mouth rinsing (t(9) = 4.918, p = 0.001) (Fig. 4). However, there was no significant difference in beta, delta, and theta power between CHO and PLB, respectively (p > 0.05).

4 Discussion The purpose of this study was to examine the changes in EEG activity following CHO mouth rinsing. The results of this study indicate there was an increase in both EEG regions and multiple EEG frequencies. However, the only significant surge of EEG activity was observed in an alpha power where the increase was recorded with the presence of CHO mouth rinsing. The increase in alpha power was observed across EEG electrode sides (F3 and T7). These results were observed in previous studies

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Fig. 4 Changes in four wave power at temporal region (T7) with CHO and PLB mouth rinsing. *Significant difference between CHO and PLB (p < 0.05)

where an increase in EEG power in the alpha, beta, delta, and theta frequencies (Bailey et al. 2008; Morinushi et al. 2000). Study in alpha power especially related to cognitive and exercise performance has been extensively expand and explored. Fundamentally, alpha activity is the best known and most commonly studied in human brain (Teplan 2002). The conditions during eye-close and eye-open are dominant in alpha activity. In addition, the conditions of relaxation and attention (Shapiro et al. 2017) as well as arousal (Fronso et al. 2016) were also previously carried out by researcher. Furthermore, motivational state can be expressed through the changes of alpha power (Robertson and Marino 2015). Despite inconsistency due to instruments and various procedure of experiments, increase in alpha wave power in relation to exercise performance is still well documented (Cheron et al. 2016). It was evident in the increase in alpha peak frequency in post-exercise (Gutmann et al. 2018). Although analyzing in brain activity has been much interpretation in terms of the changes from baseline, there were also studies make an attempt comparing the neural activity between conditions. For example, according to Büchel et al. (2021) they demonstrated significant main effect in the low alpha frequency in response to exercise. In another study, measured neural activity at occipital and parieto-occipital channels with a frequency resolution of 0.17 Hz revealed that estimates of power across the lower-frequency bands (theta: 4–8 Hz, alpha: 8–13 Hz, and beta: 16–30 Hz) significantly modulated by lowto high-intensity exercise (Büchel et al. 2021). Previous evidence showed either in changes of alpha wave or comparison the change between conditions much focuses on exercise activity. In fact, the mechanism of arousal and motivational factors in physical activity and exercise performance (Sanchis et al. 2020) is inherent. This is complemented with the research on consumption of supplement intake and exercise intensity on executive and arousal vigilance.

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Meanwhile, beta band originated with sensorimotor-related conditions found increased in the power spectrum predicted subsequent motor errors (Pluta et al. 2018). As for the delta and theta power, these two slow frequency bands investigated to measure sleep and wakefulness and only found changes in theta power (Roky et al. 2003). Meanwhile, in an exercise condition, there found significant changes from pre- to post-exercise in theta power (Choktanomsup et al. 2017). However, further discussion was limited to merely supporting previous evidence from their current findings. Several studies have been investigating the brain response via EEG activity during exercise. Study by Guimaraes et al. (2015) found that an increases in maximal effort for alpha and beta power in frontal lobe and during maximal graded exercise. These areas associated with feeling reward, position emotion, memory, and pleasure (Guimaraes et al. 2015). Similar finding also was observed during graded cycling exercise until volition exhaustion (Gutmann et al. 2018), moderate intensity exercise (Hicks et al. 2018) and 10 km cycling exercise (Spring et al. 2017). Within most frequency bands, alpha activity seems mostly reported to be a primary wave activity during exercise (although beta and other waves frequency were also reported during exercise) concomitantly to emotional responses and physical demand during exercise. Since an increase of alpha power was overserved in this study, we speculated that the present of CHO in the mouth may potentially be an ergogenic benefit during exercise performance. However, further study is warranted to verify this speculation. Another important finding in this study was that the CHO mouth rinsing produces a neural activity response to caloric content of glucose (CHO) than sweet non-caloric PLB. The alpha power for CHO solution was found to increase in both frontal and temporal regions compared to sweet non-caloric PLB (Figs. 3 and 4). Therefore, it is important to accepted caloric content rather that sweetness of neutral CHO is underlined the cortical responses of the brain activity. The responses of brain to glucose in the mouth were speculated to mediated emotional and behavioral responses which associating to rewarding stimuli and link to enhance exercise performance (Chambers et al. 2009). Therefore, the same responses in brain activity may elucidate the same response to emotion and exercise performance, however, this needs further examination. Our study herein has several limitations. The responses of the EEG activity were not limited to frontal and temporal brain regions (F3 and T7) only. This limits the understanding of the heterogeneity of the brain activity regards to which area were affected by the CHO mouth rinsing. Our participants were healthy recreational male athletes with history of several year sports involvement. Thus, this finding is associated within this characteristic and cannot be generalized to other populations such as trained athletes, patients, or non-physical subjects. As consequences, our results can only generalize to male and whether the effects found here to female has yet to be proven.

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5 Conclusion In conclusion, the significant results of brain waves speculated the prominent role of CHO towards the changes of frequency alpha power. The changes in alpha power due to CHO mouth rinsing may influence the increased of arousal and motivational level. Unlike alpha frequency that previously known to measure arousal or motivational state, other frequency band such as delta, theta, and beta found inconsistent and limited findings when trying to relate with mouth rinsing activity. Future study is warranted to investigate the brain activity changes with CHO mouth rinsing during exercise. Acknowledgements Harris Kamal Kamaruddin is thankful to Universiti Teknologi MARA Perlis for providing research funding (Dana Pembudayaan Penyelidikan Dalaman; DPPD). The authors thanks to all participants who took part in this study and to all technical staff of the Sports Engineering Research Centre, Universiti Malaysia Perlis and Exercise Physiology Laboratory, Universiti Teknologi MARA Perlis. Conflict of Interest The authors declare that they have no conflict of interest.

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Comparisons of Physical Activity Patterns in Children with Autism Spectrum Disorder and Typically Developing Children Wei Joo Chen, Ahmad Nabilatulhuda, and Nor M. F. Farah

Abstract The physical activity (PA) guidelines recommend that children and adolescents aged 6–17 years achieve at least 60 min of moderate-to-vigorous-intensity physical activity (MVPA) daily. Children with autism spectrum disorder (ASD) have neurodevelopmental impairment, therefore meeting the MVPA recommendation can be a challenge for them due to limitations in motor and social skills. This study aimed to compare PA patterns between children aged 7–12 years with ASD (mild-to-moderate severity) and typically developing (TD) children in a Malaysian sample. The Godin-Shephard Leisure-Time Physical Activity Questionnaire (proxyreporting) was used to assess time spent in MVPA, types of PA (outdoor/indoor), as well as screen time. A total of 68 children (ASD = 34, mean age: 8.7 ± 1.5 years, TD = 34, mean age: 11.0 ± 1.4 years) participated in this study. Findings showed that TD children (504 ± 232 min/week) seemed to spend more time (27%) in MVPA compared to ASD children (385 ± 167 min/week), but this difference approached non-significance (p = 0.052). However, TD children recorded higher indoor PA (6.1 ± 2.7 h/week, p < 0.001) and lower screen time (11.8 ± 7.1 h/week, p = 0.01) compared to ASD children (indoor PA: 3.3 ± 1.6 h/week, screen time: 20.2 ± 12.1 h/week). In conclusion, both children groups achieved the MVPA recommendation of at least 300 min/week, but ASD children appeared to have a higher screen time, exceeding the recommended amount of 2 h/day. This finding highlights the need of effective strategies to sustain MVPA and reduce screen time in population of children with ASD. Keywords Physical activity · Autism spectrum disorder · Development W. J. Chen (B) · N. M. F. Farah Faculty of Health Sciences, Center for Community Health Studies, Universiti Kebangsaan Malaysia, 50300 Kuala Lumpur, Malaysia e-mail: [email protected] N. M. F. Farah e-mail: [email protected] A. Nabilatulhuda Faculty of Health Sciences, Program of Occupational Therapy, Universiti Kebangsaan Malaysia, 50300 Kuala Lumpur, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_21

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1 Introduction Low levels of physical activity (PA) and sedentary behaviors have negative impact on children’s health. PA guidelines recommend children and adolescents aged 6–17 years to achieve at least 60 min of moderate-to-vigorous-intensity physical activity (MVPA) daily (Bull et al. 2020). Notably, concern should be given to a sub-group of children with autism spectrum disorder (ASD). ASD is a complex neurodevelopmental disorder characterized by impairment in motor and social communication skills, repetitive behavior patterns, and restricted interests (Memari et al. 2015; Sharma et al. 2018). A study conducted by Ministry of Health (MOH) in 2006 showed that the prevalence of ASD in Malaysia was approximately 1.6 per 1000 children aged 18–36 months (Family Health Division 2006). Due to social, communication, and behavior problems associated with ASD which can limit the opportunity for PA engagement, meeting the MVPA guidelines can be a challenge. Indeed, evidence has shown that children with ASD are less physically active and with more sedentary behavior compared to their typically developing (TD) peers (Hillier et al. 2020; McCoy and Morgan 2020; Menear and Ernest 2020). Physical inactivity can impose a higher risk of overweight and obesity among children, and in fact, Kamal Nor et al. (2019) had reported a high prevalence of overweight (11.3%) and obesity (21.9%) among Malaysian children and adolescents with ASD. PA is very beneficial for children with ASD because it not merely helps in maintaining physical health, it also aids in improving ASD traits. PA interventions have been shown to significantly improve overall executive functions, particularly on cognitive flexibility and inhibitory control (Liang et al. 2022), motor skill (Pan et al. 2017), social communication skills (Zhao and Chen 2018), metabolic profile, and quality of life, as well as decrease autism traits, particularly the stereotypical behavior (Toscano et al. 2018). Due to the importance of PA in children with ASD and the lack of published reports on PA in children with ASD in the Malaysian context, thus the aim of this study was to describe and compare PA patterns between children aged 7–12 years with ASD (mild-to-moderate severity) and typically developing (TD) children in a Malaysian sample. The findings of this study may reveal some insight regarding PA patterns in children with ASD and to highlight any deficits in PA patterns.

2 Methods 2.1 Participants This was a cross-sectional study involving 68 children (ASD = 34, TD = 34) aged 7– 12 years. Children with ASD were recruited from local occupational therapy clinics and rehabilitation centers, whereas TD children were recruited from primary schools in Kuala Lumpur. Children with ASD were diagnosed by either a pediatrician or a

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clinical psychologist. Children with physical disability, chronic disease, or diagnosed with severe ASD were excluded from this study. This study was approved by PPUKM Ethical Board Committee (JEP-2016-621). Written consent was obtained from parents prior to participation.

2.2 Measurements Sociodemographic measures and screen time. Demographic variables examined in this study included age, gender, and income of parent/guardians. Children’s screen time was also assessed through this questionnaire. Physical activity. The Godin-Shephard Leisure-Time Physical Activity Questionnaire (GSLTPAQ) was used to determine how often the children was engaged in physical activity in a typical week. Parents and teachers were used as proxies for children with ASD to complete the questionnaire, whereas TD children completed the questionnaire by themselves with the help of parents and researcher. GSLTPAQ is a 4-item self-administered questionnaire with the first three questions seeking information on the number of times one engages in mild, moderate, and strenuous LTPA bouts of at least 15 min duration in a typical week. Scores derived from the GSLTPAQ yields the overall “Leisure Score Index” using the following formula: (frequency of mild × 3 METs) + (frequency of moderate × 5 METs) + (frequency of strenuous × 9 METs). The scores were then used to compare children’s overall PA engagement. The time spent in MVPA was determined by summing up the time spent on moderate and strenuous/vigorous-intensity PA. In addition, PA was classified into six domains based on Pediatric Interest Profile (PIP) (Chien et al. 2014; Henry 2000), which included outdoor PA, indoor PA, social activity (e.g., outing with family), screen time (e.g., time spent on TV, iPad, and computer), creative activity (e.g., baking, drawing, choir, and riddle), and elective class (e.g., swimming, martial art, choir, drawing, and music).

2.3 Data Analysis Data was analyzed using IBM SPSS Statistics for Windows version 22. Unpaired t-test or Mann–Whitney test were used to compare Leisure Score Index, time spent on MVPA, type of PA, screen time, and time spent by parent to accompany children on doing physical activity, between children with ASD and TD children. Spearman Rho was used to determine the associations between time spent on MVPA with age, types of PA (i.e., outdoor activity, indoor activity), screen time, and time spent with parents. The significance level was set at 0.05.

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3 Result A total of 68 children (ASD = 34, mean age: 8.7 ± 1.5 years, TD = 34, mean age: 11.0 ± 1.4 years) participated in this study. Table 1 compared the time spent on different types of PA by children with ASD and TD children. Based on the Leisure Score Index, most children (ASD = 91%, TD = 100%) were considered as physically active (>24 METs/week). Regarding the time spent on MVPA, both children groups met the MVPA recommendation of at least 300 min/week. It also seemed that TD children (504 ± 232 min/week) spent 27% more time in MVPA compared to ASD children (385 ± 167 min/week), although this difference approached non-significance (p = 0.052). There were no significant differences on time spent in MVPA between children with ASD and TD children according to gender and age groups (7–9 and 10–12 years old). No significant differences were found on time spent on outdoor PA, social activity, elective class, and creative activity between children with ASD and TD children. However, TD children recorded higher indoor PA (364 ± 164 vs. 199 ± 93 min/week, 58.6%) and lower screen time (11.8 ± 7.1 vs. 20.2 ± 12.1 h/week, -52.5%) compared to children with ASD. The reported indoor PA performed by TD children was mainly doing house chores. Table 2 showed the correlation between MVPA and age and PA in children with ASD and TD children. Based on the result, MVPA is not correlated with age, outdoor activity, indoor activity, and screen time. Only time spent with parents correlated with MVPA among TD children. Table 1 Comparison of time spent on different types of PA between children with ASD and TD children ASD (n = 34)

TD (n = 34)

Mean ± SD

Mean ± SD

p value

Leisure score index (METs/week)

93.3 ± 50.0

110.1 ± 30.5

0.100

MVPA (min/week)

385.3 ± 167.4

503.9 ± 231.7

0.052

Outdoor PA (min/week)

383.3 ± 136.6

391.8 ± 240.6

0.086

Indoor PA (min/week)

199 ± 93

364 ± 164

0.00*

Screen time (h/week)

20.2 ± 12.1

11.8 ± 7.1

0.01*

Social activity (min/week)

360.0 ± 176.4

960 ± 189.8

0.79

Elective class (min/week)

17.6 ± 34.7

24.7 ± 33.41

0.24

Creative activity (min/week)

9.7 ± 24.6

16.1 ± 40.3

0.75

Time spent with parents (min/week)

995 ± 322

875 ± 539

0.15

PA Parameters

MVPA: moderate-to-vigorous-intensity physical activity; PA: physical activity; ASD: autism spectrum disorders; TD: typical developing; (*) indicates significant difference (p < 0.05) between ASD and TD

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Table 2 Correlation between MVPA and age and PA in children with ASD and TD children Correlates of MVPA

ASD (n = 34)

TD (n = 34)

rs

p value

rs

p value

Age

0.003

0.986

−0.254

0.147

Outdoor PA (min/week)

0.120

0.500

−0.0283

0.105

Indoor PA (min/week)

−0.060

0.737

0.161

0.363

Screen time (min/week)

−0.261

0.136

−0.199

0.259

0.188

0.286

−0.360

0.036*

Time spent with parents (min/week)

MVPA: moderate-to-vigorous-intensity physical activity; PA: physical activity; ASD: autism spectrum disorders; TD: typical developing; (*) indicates significant correlation (p < 0.05)

4 Discussion The objective of this study was to describe and compare PA patterns between children with ASD and TD children our finding showed that both children groups met the PA recommendation of 300 min/week, though it seemed that TD children spent slightly more time on MVPA compared to children with ASD. This finding shows an encouraging sign with regards to PA engagement among children with ASD as findings from western countries showed that individuals with ASD tend to spend less time on PA compared with their TD peers (Hillier et al. 2020; McCoy and Morgan 2020; Menear and Ernest 2020). The possible reasons for our findings might be due to children with ASD included in this study attended academic classes every day and followed sport and physical education several days in a week, as well as therapy in hospital or rehabilitation centers. Our hypothesis is supported by previous studies that showed that participating in school-based activities (Garcia et al. 2021) and extracurricular programs (Garcia et al. 2020) can help to increase PA levels in children with ASD. A review by Sharma et al. (2018) stated that non-pharmacological therapies such as attending therapy sessions for children with ASD have been shown to relieve ASD symptoms and improve their social skills, thereby reducing the barriers to PA participation and increasing their engagement in PA. Furthermore, McCoy and Morgan (2020) demonstrated that as ASD severity increases, the adjusted odds of PA participation decreased, as well as the risk of being overweight or obese increased. Children with mild to moderate ASD severity in this study might have less severe ASD symptoms, and thus having similar PA participation as TD children. In addition, Memari et al. (2015) reported that higher parents’ income was associated with higher PA level; therefore, children from lowincome family generally reported lower PA level than children from a higher-income family. In this study, a majority of the children with ASD came from families with median to high income. It may be speculated that family without financial constraints have the ability to bear the expenses on therapy, elective classes, as well as indoor or outdoor activity for their children.

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Another finding of the study that is worth highlighting is the higher amount of screen time recorded in children with ASD compared to TD children. Children with ASD had longer screen time (52.5%) compared to TD children, and exceeded the recommended amount of 2 h/day (Healy et al. 2019). This finding corresponds with previous studies, which showed children with ASD had longer screen time on gadgets (2 vs. 1.83 h/day) (Healy et al. 2018), watching television (4.6 vs 2.06 h/day) (Chonchaiya et al. 2011), and video games (boys: 2.4 vs. 1.6 h/day, girls: 1.8 vs. 0.8 h/day) (Mazurek and Wenstrup 2013)compared to TD children. Menear and Ernest (2020) also found that the percentage of children with screen time > 3 h/day was higher in children with ASD compared to TD children. Excessive screen time can affect children’s physiological and psychological development. Studies showed that increased screen time was associated with decreased PA level (Sandercock et al. 2012), increased body mass index (Healy et al. 2018), reduced muscle strength and gross motor skills (Domingues-Montanari 2017), reduced sleep quality (Hale et al. 2018), and decreased academic performance (Adelantado-Renau et al. 2019). In addition to that, longer screen time in children with ASD was also found to be associated with worsened ASD symptoms (esp. sensory symptoms), lower development quotients (esp. language domain) (Dong et al. 2021b), and most importantly, reduced parent–child interaction level, which could significantly affect the development of children’s social and communication skills (Dong et al. 2021a). Therefore, excessive screen time in children with ASD is a serious issue that warrants further attention.

5 Limitation Several limitations warrant against the overgeneralisation of the present findings. First, data on physical activity was collected using questionnaires instead of objectively measured using accelerometry method. For children with ASD, their parents were used as proxies in completing the questionnaires and some were unable to report the PA of their children in school as they were not present in school with their children. Similarly, some TD children had difficulty in recalling their PA even with the help of parents and researchers. This may have increased the likelihood of overreporting or under-reporting of PA in this study. Second, this study was carried out at the year-end, during which the school holidays were around the corner and many year-end school activities (e.g., examination and extracurricular programs) were being conducted, thus potentially affecting the children’s typical daily PA patterns. Another limitation was this study included a small sample size and the gender of children with ASD was uneven, as there were more male (88%) children compared to female (12%) children.

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6 Recommendation Future studies are encouraged to include objective measurement of PA such as using accelerometers. Apart from that, assessing the different types of sedentary behaviors, such as reading and performing desk activities may help to better categorize PA patterns in children.

7 Conclusion In conclusion, the children involved in this study achieved the MVPA recommendation of at least 300 min/week, although children with ASD scored slightly lower PA levels compared to children without ASD. Children with ASD also appeared to have a higher screen time, exceeding the recommended amount of 2 h/day, thus highlighting the need of interventions to curb excessive screen time in this population. Lifestyle and behavior modification programs should also focus on increasing awareness on PA among parents, clinicians, and educators in order to promote higher engagement PA as well as reducing screen time for children with ASD.

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Effects of Core Stability Training Among Low Back Pain Malaysian Elite Sailor Athletes Nurul Afiqah Bakar, Wan Amirul Hafiy Wan Rosli, Nur Firzanah Azrul Hisham, and Nurul Hidayah Amir

Abstract Sailors who engage in continuous hiking method have increased the risk of spine and lower extremities injuries due to resulting high pressure on the lumbar spine and intervertebral disc. Objective: The study was to investigate the effects of a six-week core stability training (CST) on 2000-m rowing performance, isometric back leg strength and flexor endurance among elite sailing athlete. Eight male elite sailing athletes with no musculoskeletal disorder, aged 21 ± 2.14 years old were involved in this study. Participants were separated into two groups: CST (n = 4) and control group (CON) (n = 4). This study using randomized control trial design. Paired t-test was used to compare pre and post of visual analogue scale (VAS), 2000m rowing performance, isometric back leg strength, and flexor endurance. There was a significant effect on core stability training group when compared for pre and post VAS, (p < 0.05). However, there were no significant differences between 2000-m rowing, isometric back leg strength, and flexor endurance between CON and CST groups. It would seem that the type of core training programme used in this study could be beneficial by consistent developments in core endurance and may also be significant in preventing and reducing LBP occurrences. However, this study has still not been convincing in finding a relationship between training of the core and enhancements in physical execution. Keywords Injury prevention · Core stability training · Musculoskeletal · Low back pain · Malaysian sailor athletes

1 Introduction Sailing is a competitive sport, requiring elevated amount of physical conditioning and specialized capability as to perform effectively (Schultz et al. 2016). The study N. A. Bakar (B) · W. A. H. W. Rosli · N. F. A. Hisham · N. H. Amir Faculty of Sport Science and Recreation, Universiti Teknologi MARA (UiTM), Arau, Perlis, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_22

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stated that in sailing, there are many types of vessels (single or double, with or without trapeze, mono hull or multi hull, etc.) all of which require some small adjustments in their navigation, but a technical aspect which does not change from one boat to another is the hiking technique for which the vessels have an adaptation called a toe strap (Chicoy and Encarnación-Martínez 2015). This technique is a special manoeuver by which sailor leans back, in part or in full, over the edge of the boat, in a horizontal position, holding their legs fastened to the toe strap (Chicoy and Encarnación-Martínez 2015). Hiking is a technique in sailing when the sailor inclined outside of the boat to keep up its upstanding position in order to augmenting the forward speed of the boat (Schultz et al. 2016). Hiking requires high forces generated by lower extremities and trunk, potentially producing high lumbar spine compression and shear loads linked to acute low back pain. To stabilize the boat, counteracting the wind’s motion on the sails, the sailor keeps their feet hooked under the toe strap close to the boat’s centreline and keeping the upper part or body above the boat’s edge to exert sufficient force to keep the boat upright (Chicoy and Encarnación-Martínez 2015). The risks of injury to the spine and lower extremity are more prominent in classes that require the sailor to take part in continuous hiking (Schultz et al. 2016). The quadriceps are the most involved in the hiking technique in either of the three positions, accompanied by the rectus abdominis, which increases its participation proportionately to the wind speed (Chicoy and Encarnación-Martínez 2015; Sekulic et al. 2006). In other words, if the sailors lean back in the hiking position, it works well. Besides, based on a study by Berge and colleague (2017), it was revealed that hiking and unloading forces might be causes for lower back pain prior to and during Olympic class regattas. According to Trompeter and colleague (2017), it has shown that elite sailing athletes spent most of their time with training and competition, and their bodies have to bargain with mechanical strain and thus putting their musculoskeletal system in a great level of stress. Besides, back pain also has been reported to be more common in sports with high spinal loads than other sports, as well as non-athletes (Stuber et al. 2014). Specifically, in sailing, the most often injury has been reported in Olympic class sailing is low back pain that considered up to 53% from all of the injuries (Logan et al. 2014).

1.1 Problem Statement Based on Schultz et al. (2016), the risk of injury of the spine and lower extremity is more prominent in classes that require the sailor to take part in continuous hiking due to subsequent high pressure and shearing forces follow-up on the lumbar spine and intervertebral disc, along these lines conceivably expanding the risk of injury. However, the other study has shown that the improvement in core muscle strength did not mean to improve athletic execution in either running or rowing because of they do not engage of any measures for core muscle strength or endurance (Medica et al. 2018). Although core stability training (CST) is effective in treating athletes

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with low back pain (LBP), the findings of the research made it impossible to say definitively which core stability training methods are the most effective (Stuber et al. 2014). Despite from similar finding of Medica et al. (2018), it has estimated that maximal isometric strength and perseverance of the core muscles would increase after CST and would join by an expansion in throwing velocity while standing and jump throws. Therefore, this study is intended to evaluate the effects of six weeks of core stability training (CST) intervention on 2000-m rowing performance, isometric back leg strength, and flexor endurance among elite sailing athletes.

2 Methodology 2.1 Research Design This study involved quantitative research using a randomized control trial design to assess the effect of a six-week core stability training (CST) intervention on rowing performance, isometric back leg strength, and flexor endurance as injury prevention from low back pain among Malaysian sailing athletes. The athletes were randomized to either an experimental (CST) or control (CON) group.

2.2 Participants Eight out of twenty-five male elite sailing athletes have been selected to participate in this study. The inclusion criteria for the study were: (a) participants must have at least two years of sailing experiences from national sailing squad in Kompleks Sukan Perahu Layar Kebangsaan, Langkawi, Kedah; and (b) participants must continue to participate in the same weekly sailing program, which incorporated a minimum of 6 h of physical activity per week. Participants were excluded if they were diagnosed by a physician with any severe musculoskeletal disorder such as spondylolisthesis (slip of low back vertebra) and cauda equine syndrome (swelling of the end nerves of the spinal cord). Participants who were unable to complete 50% of the experimental procedures while were also excluded. Participants were made to understand their right to withdraw from this experimental. All study protocols data collection procedures were approved by UiTM Research Committee.

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2.3 Sample Size A sample of eight male elite sailing athletes on CST and CON group will be sufficient for this experimental trial to detect a difference of 10% between treatment. Group intervention with 80% power and at 5% significant level (Dupont and Plummer 1998). The 90% difference represents the expected difference in effects of core stability training that will be measured by 2000 m rowing, isometric back leg strength, and core endurance between group for pre- and post-test intervention.

2.4 Research Procedure Visit 1: Participant Preparation Participants were asked to fill up informed consent and health screening medical examination performed by a medical officer (PAR-Q) one week before any test preliminaries. The detail procedures and potential benefit were explained clearly to the participants. Participants were having breakfast 2 h prior to the experiment. The effects of core stability subjects were measured by isometric back leg strength, core endurance test, and 2000-m rowing test. Visit 2: Anthropometry measurement The first visit of pre-test in week one comprised anthropometric measurements of height (with accuracy 0.5 cm) and body weight (with accuracy 0.5 kg) utilized by an electronic digital scale. Pre-test Outcome Measurement Participants arrived at the laboratory at 0900 h. Then, participants completed breakfast 2 h prior to the experiment and conducted for a pre-test intervention. All standard tests were performed in randomized order on one test days. Then, participants have proceeded to visual analogue scale (VAS) which participants have to draw a vertical mark on each line to indicate their current level of lower back pain (Boonstra et al. 2008; Kasmi et al. 2017). Next, participants required to proceed for 2000-m rowing test where the test estimated in minute (Kasmi et al. 2017). Then, continue with isometric back leg strength tests when an external force was applied to a handle, which attached to an adjustable chain, a steel spring compresses, and a pointer moves. For the test, the length of the chain has been adjusted to the participant height by asked the subject to stand on the base of BLC dynamometer with extended knees. Subsequently, the handle was positioned at the height of the intra-articular space of the knee joint. For the test, participants have to stand on the base, with knees and hip flexed slightly, while the lower back needs to maintain an appropriate lordotic curve. Participants have to lift in a vertical direction by providing a continuous isometric contraction of the extensors of the knees, hips, and lower back while holding the handle. This test method was adopted by Ten Hoor and colleague (Hoor et al. 2016).

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Finally, participants have to proceed with flexor endurance test where the test evaluates anterior core muscles. It was directed through recording the time the participant held a situated torso flexion position against gravity. The torso was flexed at 60°, and the knees and hips flexed at 90°. The toes were secured by the analyst. Failure was distinct as when the participant’s torso fell below 60° (Abdallah et al. 2019). Visit 3, 4, 5, 6, 7, 8: Core Stability Training Intervention Participants were separated into two groups: (CST) and (CON). The CST group carried out the intervention two times a week for six consecutive weeks. Every session started with a general 10-min warm up. The CST comprised of eight specific core and rotational exercises for the ventral, dorsal, and lateral core muscle chain executed in closed kinetic chain on a progressively unstable surfaces such as balance pad, gymnastic ball and foam roll. Training intensity was increased by adding load to increase the degree of instability, for example, one or two of body parts on balance pad, gym ball or foam roll. Each exercise was performed in two sets, each for 45 s with 1-min rest between sets. The participants were requested to execute as many as repetition as possible within 45 s. An experienced strength coach was present during each training session to guarantee exercises movement are performed accurately. Training intensity was expanded each second of training sessions by changing the complexity of movement from a static to dynamic exercise. All participants from the CST group will participate in at least 10 to 12 sessions throughout the six weeks. None of the CON group participants underwent any training either previous or during intervention periods. This training protocol was adopted from Medica et al. (2018). Visit 9: Post-test Outcome Measurement Participants were arrived as the same time as they did during pre-test measurement. Participants completed breakfast 2 h prior to the post-test measurement session. Participants performed standardized warm-up. Then, participants have proceeded to complete the visual analogue scale (VAS), 2000-m rowing test, and isometric back leg strength and flexor endurance test.

2.5 Statistical Analysis All results were presented as mean ± standard deviation. Normality of all data were confirmed used visual inspection of skewness, kurtosis and Shapiro–Wilk statistic. Paired T-test was used to compare the effects of core stability training for pre and post-test on 2000-m rowing performance, isometric back leg strength and flexor endurance. All data in this study were analysed using the IBM SPSS Statistic version 25.0 (IBM Corporation, Chicago II, USA).

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Table 1 Physical characteristics of participants Variables

CST (n = 4) Mean ± SD

CON (n = 4) Mean ± SD

Total (n = 8) Mean ± SD

Age (y/o)

20 ± 2.16

22 ± 1.8

21 ± 2.14

Height (cm)

172 ± 4.7

173.3 ± 4.2

172.6 ± 4.2

Weight (kg)

65.7 ± 6.7

74.1 ± 6.5

69.9 ± 7.6

22.2 ± 1.8

24.6 ± 1.1

23.4 ± 1.9

BMI

(kg/m2 )

Notes Values are presented as Mean ± SD BMI Body Mass Index

3 Results 3.1 Physical Characteristics of Participants The physical characteristics of eight male elite sailing athletes are presented in Table 1.

3.2 Pain Threshold Based on Fig. 1, a paired sample t-test was conducted to compare pre- and post-test between groups and within group of control group (CON) and core stability training (CST). There was no significant differences on both group (0.5 ± 3.7) for pre-test of VAS, t (3) = 0.3, (p > 0.05, p = 0.804). There was no significant differences on CON and CST (2.5 ± 2.1) for post-test of VAS, t (3) = 2.4, (p > 0.05, p = 0.096). However, when compared within groups, there was significant effects only on CST (2.25 ± 0.95) for pre- and post-test of VAS t (3) = 4.7, (p < 0.05, p = 0.018). However, there was no significant effects on CON (0.25 ± 1.71) for pre- and post-test of VAS t (3) = 0.293, (p > 0.05, p = 0.789).

3.3 2000-m Rowing Performance Based on Fig. 2, a paired sample t-test was conducted to compare pre- and post-test between groups and within group of control group (CON) and core stability training (CST). When compared between CON and CST for pre-test of 2000-m rowing test (0.2 ± 0.7), there was no significant differences t (3) = 0.4, (p > 0.05, p = 0.709) for both groups. There was no significant differences on CON and CST (0.8 ± 0.7) for post-test of 2000-m rowing test t (3) = 0.3, (p > 0.05, p = 0.817). Furthermore, there was no significant effects on CON for (0.05 ± 0.07 min) and CST (0.19 ± 0.14

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Fig. 1 Visual analogue scale between CON and CST

min) pre- and post-test of 2000-m rowing, t (3) = 1.372, (p > 0.05, p = 0.264), t (3) = 2.633, (p > 0.05, p = 0.078). These results show that core stability training does not have an effect for both group on 2000-m rowing performance.

Fig. 2. 2000-m rowing performance between CON and CST

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Fig. 3 Isometric back leg strength between CON and CST

3.4 Isometric Back-Leg Strength Based on Fig. 3, a paired sample t-test was conducted to compare pre- and post-test between and within group. For CON and CST (1.8 ± 11.8) for pre-test of isometric back leg strength, there was no significant differences for both group t (3) = 0.3, (p > 0.05, p = 0.787). However, when compared between CON and CST (25.0 ± 15.4) for post-test of isometric back leg strength, there was a significant difference which p-values, t (3) = 3.3, (p < 0.05, p = 0.047). Moreover, there was no significant difference on control group (2.75 ± 6.24) and core stability training (24.0 ± 15.4) for pre- and post-test of isometric back leg strength, t (3) = 0.882, (p > 0.05, p = 0.443), t (3) = 3.107, (p > 0.05, p = 0.053). These results advocated that core stability training does not have an effect on isometric back leg strength for both groups.

3.5 Flexor Endurance Based on Fig. 4, a paired sample t-test was conducted to compare pre- and posttest between and within groups of control (CON) and core stability training (CST). There was no significant differences for both group (0.2 ± 0.6) for pre-test of flexor endurance t (3) = 0.6, (p < 0.05, p = 0.585). For post-test of flexor endurance, there was no significant differences between both groups t (3) = 1.3, (p < 0.05, p = 0.295).

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Fig. 4 Flexor endurance between CON and CST

Lastly, there was no significant effects on both group for pre- and post-test of flexor endurance, t (3) = 1.529, (p > 0.05, p = 0.224) t (3) = 1.531, (p > 0.05, p = 0.165). These results show that core stability training does not have an effect on the flexor endurance for both groups.

4 Discussion 4.1 Pain Threshold Due to back pain in large boat sailing is associated with crew positions, such as winch man experiencing repetitive movement and lateral grinding pressure or bowman and sewer man lifting spinnaker poles and heavy sails (Allen and Jong 2006). For comparison within groups, there was a no significant effects on control group for pre- and post-test of VAS. However, there was an effect on core stability training group for pre- and post-test of VAS. The significant effects might be due to the back pain that has been reported to be more common in sports with high spinal loads than other sports, as well as non-athletes (Stuber et al. 2014). It shows that there was constrained research to help on injury prevention programmes in sailing sports.

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4.2 Rowing Performance It usually involves on achieving the perceived ideal weight for racing a small boat or meeting the weight limits of a single design class (Allen and Jong 2006). When compared within groups, there was no significant effects on CON and CST for preand post-test of 2000-m rowing. These results show that core stability training does not have an effect for both group on 2000-m rowing performance. This may due to of various factors. Firstly, the intervention program, we completed did not yield the enhancements in core endurance that we had anticipated. Elite sailing athlete were highly trained athlete which they spent most of their time–training, they also devote their time to participating in specific activities regarded to be the most applicable to develop the fundamental component skills for expert performance (Baker et al. 2003).

4.3 Isometric Back Strength The significant differences might be due to level of training improvement (i.e., trainability) is restricted by genetic factors. For results within groups, there was no significant difference on control group and core stability training for pre- and post-test of isometric back leg strength. These results advocated that core stability training does not affect isometric back-leg strength. However, core stability training might have improved for an elite sailing athlete on isometric back leg strength. It might be due to the athlete may have less motivation to perform the post-test to maximal effort.

4.4 Flexor Endurance For post-test of flexor endurance, there was no significant differences between both groups. In the flexor endurance test, motivation levels, self-efficacy and body mass index have all been shown to influence a person’s holding time (Evans et al. 2007). When compared within groups, the results shows that there were no significant effects on both group for pre and post-test of flexor endurance. This might due to sailing sports have different boat classes, crew positions and baseline fitness levels make it unfeasible to give a uniform suggestion for wellness prerequisites.

5 Conclusion While this study revealed a significant improvement in only one marker which is pain threshold on CST group, it is also worth noting that CST group demonstrated good

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effect on isometric back leg strength and improves core stability. Developments in core endurance may also be prominent in preventing and reducing occurrences of LBP. Meanwhile, CON group demonstrated (although not statistically significant) that specific training is crucial for improving sports performance. CST should be included in all types of physical or contact sport as core stability are very important to enhance movement and performance.

References Abdallah AA, Mohamed NA, Hegazy MA (2019) A comparative study of core musculature endurance and strength between soccer players with and without lower extremity sprain and strain injury. Int J Sports Phys Ther 14(4):525–536 Allen JB, De Jong MR (2006) Sailing and sports medicine: a literature review. Commentary. Br J Sports Med 40(7):587–593 Baker J, Horton S, Robertson-Wilson J, Wall M (2003) Nurturing sport expertise: factors influencing the development of elite athlete. J Sports Sci Med Berge HM, Anderson TE, Bahr R (2017) Monaco abstracts. In: IOC world conference on prevention of injury and illness in sport, 97372 Boonstra AM, Preuper HR, Reneman MF, Posthumus JB, Stewart RE (2008) Reliability and validity of the visual analogue scale for disability in patients with chronic musculoskeletal pain. Int J Rehab Res 31(2):165–169 Chicoy I, Encarnación-Martínez A (2015) Determining factors in the performance of hiking in dinghy sailing: a literature review Ion Chicoy; Alberto EncarnaciónMartínez. J Sports Sci 25(2):3–19 Dupont WD, Plummer WD (1998) Power and sample size calculations for studies involving linear regression, pp 589–601 Evans K, Refshauge KM, Adams R (2007) Trunk muscle endurance tests: reliability, and gender differences in athletes. J Sci Med Sport 10(6):447–455 Kasmi S, Hammami A, Noureddine G, Riadh K (2017) The effects of Nordic hamstring exercise on pain and performance in elite rowers with lower back pain. Turk J Kinesiol 3(2):22–25 Logan P, Blackburn M, Schultz A, Lockie R, White D, Taaffe D (2014) Musculoskeletal screening as a predictor of seasonal low back pain in Olympic class sailors. J Sci Med Sport 18:e77 Medica EM, Kuhn L, Weberruß H, Horstmann T, Edizioni C, Medica M (2018) Effects of core stability training on throwing velocity and core strength in female handball players Core resistance training for throwing velocity in handball Chair of Preventive pediatric, Department. J Sports Med Phys Fitness 59(9):1479–1486 Schultz AB, Taaffe DR, Blackburn M, Logan P, White D, Drew M, Lockie RG (2016) Musculoskeletal screening as a predictor of seasonal injury in elite Olympic class sailors. J Sci Med Sport 19(11):903–909 Sekulic D, Medved V, Rausavljevi N (2006) EMG analysis of muscle load during simulation of characteristic postures in dinghy sailing. J Sports Med Phys Fitness Turin 46(1):20–27 Stuber KJ, Bruno P, Sajko S, Hayden JA (2014) Core stability exercises for low back pain in athletes. Clin J Sport Med 24(6):448–456 Ten Hoor GA, Musch K, Meijer K, Plasqui G (2016) Test-retest reproducibility and validity of the back-leg-chest strength measurements. Isokinet Exerc Sci 24(3):209–216 Trompeter K, Fett D, Platen P (2017) Prevalence of back pain in sports: a systematic review of the literature. Sports Med 47(6):1183–1207

Comparison of Ballet Barre and Center Training on Lower-Limb Active Flexibility and Dynamic Balance in Young Recreational Rhythmic Gymnasts See Beatrice Qin Thon and Kok Lian-Yee Abstract Ballet training has been recommended as part of rhythmic gymnasts’ physical training repertoire as it has been found to develop aspects such as aesthetics, poise and elegance which can bring about improved gymnastic performance. The aim of this study was to compare two types of ballet training – ballet barre and center training – on lower-limb active flexibility and dynamic balance in young recreational rhythmic gymnasts. Rhythmic gymnasts from a dance academy (n = 21; age = 11.52 ± 1.83y; weight = 32.58 ± 9.84 kg; height = 140.10 ± 11.17 cm; training experience = 5 ± 1.64y) participated in this study. Participants were assigned into barre (n = 11) and center (n = 10) experimental groups for respective experimental training in addition to the usual gymnastic training regimen twice a week over a 6-week duration. Pre- and post-tests were conducted to determine participants’ active flexibility and dynamic balance. Active flexibility was measured via unassisted front-split (FS, hip flexion), side-split (SS, hip abduction) and Pench´e (P, hip extension) tests, while dynamic balance was assessed through side-kick (SK, frontal plane) and Arabesque to Pass´e (AP, sagittal plane) tests. Paired sample t-test analysis indicated significant main effect improvement in active flexibility for both experimental groups after training intervention (FS: p = 0.000, SS: p = 0.000; P: p = 0.000), but no significant interaction effects were detected. Similarly for dynamic balance, no significant differences were noted between training modes (SK: p = 0.280; AP: p = 0.383), with both experimental groups achieving statistically significant improvements (SK: p = 0.003; AP: p = 0.003) over the training duration. The present findings suggest that both types of ballet training are appropriate supplementary training for young rhythmic gymnasts. Keywords Ballet training · Barre training · Center training · Active flexibility · Dynamic balance S. Beatrice Qin Thon (B) · K. Lian-Yee Faculty of Applied Science, Tunku Abdul Rahman University of Management and Technology, Kuala Lumpur, Malaysia e-mail: [email protected] K. Lian-Yee e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_23

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1 Introduction Rhythmic gymnastics (RG) is considered as one of the most complex artistic and aesthetic sport which combines the elements of gymnastics, classical ballet and dance with apparatus manipulation including rope, ball, hoop, clubs and ribbon that emphasizes artistic expression and technical perfection of complex movements (Belão et al. 2019; Bobo-Arce and Méndez-Rial 2013). Over the years, ballet training programs have been implemented as part of the training regimen for a diverse range of sports that rely heavily on the aesthetic aspects of movement such as figure skating (Vieira De Jesus 2013), artistic swimming (Wang 2020), artistic gymnastics (Nunomura et al. 2009; Ren 2013) as well as dance-related sports such as modern (Dipasquale and Wood 2016; Wehmeyer and Weaver 2021), Latin (Liu 2019), and ballroom (Zhang 2020) dancing, and also cheerleading (Sheng 2021). The influence of ballet on RG is noticeable as ballet movements such as passé, plié, jeté, and pirouettes have often been inserted in the training and competition routines of rhythmic gymnasts, indicating the importance of ballet training for improving RG movements (Donti et al. 2016). Previous findings revealed that ballet exercises could refine and improve the movements performed by rhythmic gymnasts by promoting a greater range of motion while stabilizing the body (Batista et al. 2018; Martinell 2009). In RG, the degree of technical and artistic perfection is greatly impacted by the ability of gymnasts to achieve and maintain their maximum range of motion (ROM) during the execution of the technical elements stated in the evaluation and judging system of the sport, commonly known as the Code of Points (CoP). The achievement of maximum ROM in RG is greatly dependent on active flexibility. Active flexibility refers to the individual’s ability to maintain or increase tension in the agonistic muscles that are shortened as a limb is moved to extreme positions without external assistance (Donti et al. 2016; Sands et al. 2016). It has been suggested that active hip flexibility is a main contributing component to higher artistic scores in young rhythmic gymnasts (Kritikou et al. 2017). In terms of maintenance of ROM another component known as dynamic balance is needed. Dynamic balance is the ability of body to maintain equilibrium while the body or parts of the body are in motion. It also includes the capability to optimally produce, transfer and control force and motion in order to maintain or regain a stable position while performing a specific task (O’Sullivan and Portnry 2014). For instance, dynamic balance contributes to the ability to perform higher number of rotations, which is one of the most important body difficulties in RG (Pluemthanom et al. 2015). This emphasizes that the ability of individuals to balance their bodies is highly correlated to the development of specialized motor habits in conjunction with complex technical elements which in turn, contributes to better performance (Sobera and Rutkowska-Kucharska 2019). Most previous studies related to the efficacy of ballet training on RG incorporated the entire standard set of ballet training which consisted of separate modes such as barre training, center work, adagio, allegro, and reverence (Fong et al. 2018; Letton et al. 2020). These studies could not determine the effectiveness of each mode within ballet training. Barre training is a series of exercises typically conducted at

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the beginning of a ballet class and serve as the foundation for the following training segments. Barre training focuses on low-impact isometric movements performed with high repetitions (Devito and Halfpapp 2015) and supposedly prepares the ballerina’s body for complex exercises that follow while sculpturing and strengthening the entire body (Paskevska 2004). It emphasizes proper body position and alignment to promote stability and mobility while giving attention to both working and supporting sides of the body (Paskevska 2005). Center exercises refer to the second mode of standard ballet training after the barre session where similar exercises performed at the barre will be repeated but without any form of external support. This mode is performed mainly using active flexibility, with the main purpose of refining technique, flexibility, balance and coordination. Center exercises comprise a series of complex dynamic movements which combine the techniques and skills performed during barre training (Kassing 2013). Contrasting results have been reported for barre and center training with a few studies suggesting that barre training better developed strength, flexibility and stability that optimized self-confidence and self-awareness (Bläsing et al. 2012; Camp 2015), while other studies found that barre training induced greater joint torque and dynamic malalignment while inhibiting complete muscle activation and the body’s natural shifting motion (Krasnow et al. 2012; Martinell 2009). Studies that focused on ballet training that devoted excessive amounts of time on barre and center exercise found that these two modes failed to develop appropriate strategies for unsupported and traveling movements which is greatly needed during actual stage performance (Wilmerding and Krasnow 2011). With the lack of certainty of the contribution and efficacy of barre and center training, this study attempted to compare the efficiency of ballet barre training and center training on the development of lower-limb active flexibility and dynamic balance in recreational rhythmic gymnasts.

2 Methods 2.1 Participants As a priori analysis indicated that a minimum of 24 participants is needed based on an alpha (α) and statistical power of 0.05 and 0.95 respectively, 26 female recreational rhythmic gymnasts from a dance academy were recruited. The gymnasts were aged between 9 and 15 years, had a minimum of two training sessions per week, and they competed at club-level competitions. All participants were free from any form of lower-limb musculoskeletal injury prior to or during the intervention period and refrained from participating in any other intervention programs during the experimental period. The participants completed a pre-test battery that consisted of three active flexibility and two dynamic balance tests. Data from the pre-test battery were converted to z-scores, and the participants were put into two experimental groups using the

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Table 1 Participants’ information (mean ± SD) Whole Sample

Barre Training Group (BTG)

Center Training Group (CTG)

(n = 21)

(n = 11)

(n = 10)

Age (y)

11.52 ± 1.83

11.64 ± 1.80

11.40 ± 1.96

Weight (kg)

32.58 ± 9.84

33.26 ± 12.29

31.82 ± 6.78

Height (cm)

140.10 ± 11.17

137.59 ± 10.71

142.85 ± 11.56

Year(s) of Experience in Rhythmic Gymnastic

5.00 ± 1.64

4.73 ± 1.49

5.30 ± 1.83

Number of Training Session(s) Per Week

3.86 ± 1.39

3.73 ± 1.42

4.0 ± 1.41

A-B-B-A technique to ensure both groups were of similar ability at the start of the experiment. The two groups were then randomly assigned to barre (BTG) or center (CTG) training, with 13 participants in each group. Unfortunately, five participants dropped out during the intervention period with 21 participants (BTG, n = 11; CTG, n = 10) completing the experiment. The participants were not compensated for their involvement, and their details are shown in Table 1.

2.2 Procedure Pre-intervention. Written informed consent was obtained from participants and their parents/legal guardians after they were briefed on the procedures. Participants were required to provide their background information while height and weight were measured and recorded. Participants underwent pre- and post-tests which were conducted one week prior to and two days after the conclusion of the intervention phase respectively. Testing procedures included a standardized stretching routine similar to their usual training, familiarization of testing procedures and five tests followed by a cool-down routine. Tests were conducted according to the following sequence: (1) unassisted front-split active flexibility test (FS), (2) unassisted sidesplit active flexibility test (SS), (3) unassisted Penché active flexibility test (P), (4) side-kick dynamic balance test (SK), and (5) Arabesque to Passé dynamic balance test (AP). Barre Training (BTG) or Center Training (CTG) groups were then formed (as described earlier) and participants were familiarized with the experimental movements by a certified rhythmic gymnastics and ballet coach. Intervention. In addition to regular RG training, both groups underwent respective interventions (Table 2) after their standardized warm-up stretching sessions. After performing the intervention training, participants continued with technical training and a cool down session. Intervention was performed twice a week over a 6-week duration for approximately 25–30 min per session. Both groups performed

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a similar training routine utilizing pre-recorded music under the guidance of certified instructors who provided physical demonstrations and verbal cues. The only difference between the groups was the intervention programs. Both intervention programs were essentially the same, differing in that one group (BTG) performed the exercises using the barre while the other group (CTG) performed similar movements without the barre. Progressions were adjusted by the instructors by gradually increasing the tempo, the difficulty, and the quality of movements on a biweekly basis. Active Flexibility Tests (Figure 1). Test data were obtained from videos taken as participants performed dominant hip flexion via the unassisted front-split (FS) Table 2 Programme structure of the 6 weeks barre training and center training No.

Name of Exercise Duration

Tempo

Sets W1S1

W1S2

W2S1

W2S2

1

Plié

1 min 03 s

Andate (76–108 bpm)

2

3

3

3

2

Échappé

42 s

Allegro (120–168 bpm)

2

3

3

3

3

Adagio (1)

54 s

Allegro (120–168 bpm)

2

3

3

3

4

Grand Battement Jeté (1)

56 s

Andate (76–108 bpm)

–

–

2

3

W3S1

W3S2

W4S1

W4S2

1

Retire and Pirouette

1 min 12 s

Andate (76–108 bpm)

2

3

3

3

2

Adagio (2)

1 min 17 s

Allegro (120–168 bpm)

2

3

3

3

3

Grand Battement Jeté (2)

1 min 26 s

Andate (76–108 bpm)

2

3

3

3

4

Échappé

42 s

Allegro (120–168 bpm)

–

–

2

3

5

Adagio (1)

54 s

Allegro (120–168 bpm)

–

–

2

3

W5S1

W5S2

W6S1

W6S2

1

Battement Tendu Jeté

1 min 28 s

Andate (76–108 bpm)

2

3

3

3

2

Adagio (3)

2 mins 25 s

Andate (76–108 bpm)

2

3

3

3

3

Grand Battement Jeté (3)

1 min 32 s

Andate (76–108 bpm)

2

3

3

3

4

Adagio (2)

1 min 17 s

Allegro (120–168 bpm)

–

–

2

3

5

Grand Battement Jeté (2)

1 min 26 s

Andate (76–108 bpm)

–

–

2

3

*

Note W = week; S = session

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Fig. 1 Active flexibility tests

test, whereas dominant hip abduction was measured by unassisted side-split (SS) test. The unassisted Penché test was conducted to determine non-dominant hip extension (Batista-Santos et al. 2015; Örs and Tursak 2020) using computerized photogrammetry [iPhone 12 (Apple Inc., Macau/Hong Kong) camera with 1080 pixels at 60 frame per second (fps)] and Kinovea software (version 0.9.5). The video camera was placed perpendicular (90°) to the center point of the participants’ hips at a distance of 3 m with a height of 80 cm (Ferri-Caruana et al. 2020). Fluorescent orange dot stickers were placed at several anatomical points including the medial malleolus of the supporting leg, and also the medial malleolus, lateral malleolus, talus and anterior superior iliac of the lifting leg. During the tests, participants were required to raise their lifting leg actively toward the intended direction until the maximum range of motion (ROM) was reached without any external assistance. Both knees were locked while maintaining a vertical upright torso (FS and SS) or horizontal torso parallel to the ground (P) throughout the entire test. A total of three attempts for maximal hip ROM were allowed, and the average result of the three trials (measured in degrees) was taken for data analysis. Dynamic Balance Tests (Figure 2). Dynamic balance was assessed through the side-kick (SK, frontal plane) and Arabesque to Pass´e (AP, frontal plane) dynamic balance test (Palomares et al. 2019). Three attempts were allowed for each test, and the average result of three trials was taken for data analysis. During the SK test, each participant was instructed to perform 10 kicking movements by lifting the dominant leg upwards and laterally to the side until reaching maximum ROM. This was immediately followed by the raising of the supporting heel off the ground and holding the posture as long as possible. The participant was allowed grab the lifting heel and pull it closer toward the trunk. Videos of the participants performing the test were recorded, and the total time in a static position was determined using the Kinovea software. The stopwatch was started once a participants raised her supporting heel off the ground while maintaining a side split posture after completing the tenth kick, whereas the stopwatch was stopped once the participant lost balance and failed to

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Fig. 2 Dynamic balance tests

maintain the posture (that is, the lifting leg falls on to the ground and/or touches the ground with any part of the body). In the AP test, dynamic balance in the sagittal plane was assessed through the maximum number of continuous repetitions without falling down or failing to maintain controlled posture. A single successful repetition began with the lifting of the dominant leg backwards and upwards until reaching an arabesque position at a height parallel (90°) to the ground, followed by bringing the leg forwards to a front passé position and a front horizontal position parallel to the ground before returning to the front passé position followed by extending the leg back to the arabesque position.

2.3 Statistical Analysis All data were analyzed using IBM Statistical Package for Social Science (IBM SPSS) for Windows, Version 20.0.0 (Armonk, NY: IBM Corp). Data for all variables were presented as means ± standard deviation (SD), while improvement in active flexibility and dynamic balance after the intervention was expressed in percentage (%). Test–retest reliability of all five tests was calculate using Pearson correlation coefficient during the pilot test. Paired sample t-tests were used to determine the significance of within-group differences for active flexibility and dynamic balance. Independent sample t-tests were utilized to measure significance of between-group differences between BTG and CTG performances. Statistical significance level was set at p < 0.05.

3 Results Paired sample t-test analysis showed significant differences in the pre-test and posttest scores within BTG (FS: p = 0.009, SS: p = 0.005; P: p = 0.004; SK, p =

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0.033; AP: p = 0.016; Table 3), suggesting significant main effect improvement of active flexibility and dynamic balance were observed after the 6 weeks barre training intervention. In CTG, statistically significant improvements were suggested in only active flexibility (p < 0.05) as insignificant improvements were detected for dynamic balance (SK: p = 0.061; AP: p = 0.384). However, independent sample t-test analysis indicated no significant differences were noted between both training modes in all tests (FS: p = 0.466, SS: p = 0.770; P: p = 0.364; SK: p = 0.280; AP: p = 0.383; Table 4).

4 Discussion The purpose of this study was to compare the efficiency of ballet barre training and center training on lower-limb active flexibility and dynamic balance in recreational rhythmic gymnasts. The key findings of this study indicated that beneficial effects in active flexibility were associated with both intervention programs, whereas only barre training resulted in significant improvement in dynamic balance. However, no significant differences in improvement were suggested between both training modes. The current findings suggested that 6 weeks of ballet barre and center training is aligned with previous findings (Dipasquale and Wood 2016) that indicated significant improvements in hip extensor flexibility during passive straight leg raise (PSLR) among novice dancers who underwent classical ballet training and contemporary dance training. Previous studies also reported that flexibility was found to improve significantly among the cheerleaders after 8 weeks of additional ballet training were programmed into regular dance cheerleading training (Zhou 2020). Possible reasons why ballet seemed to have induced positive flexibility adaptations may be because classical ballet techniques impose maximal contribution from active external hip (turnout position), in additional to knee and ankle rotation (Sherman et al. 2014). Ballet training also initiates the active contraction of the gluteus maximus and deep external rotator muscles including the piriformis, obturator internus, obturator externus, quadratus femoris, gemellus superior, and gemellus inferior which further maximize the hip flexibility (Gorwa et al. 2020). It is supported that ballet movements such as the grand battement devant and arabesque are considered atypical human movements, and these complex movement patterns promote swift physical adaptations as repetitive hip flexion created a cycle of dynamic hamstring stretching throughout the intervention session that allowed for higher leg elevations (Dipasquale and Wood 2016). The insignificant difference found between BTG and CTG could be due to both experimental groups being similarly untrained in active flexibility and unused to these forms of active flexibility training. The principle of diminishing returns stipulate that higher levels of improvement are usually observed in those who are less trained in a specific variable, in this case, active flexibility. Similarly with active flexibility, significant improvement in dynamic balance was observed for the whole sample, without significant differences between experimental groups suggesting that barre and center training benefited the rhythmic gymnasts’

156.76 ± 15.49

162.76 ± 13.33

146.09 ± 17.46

150.94 ± 16.88

Unassisted side-split (°)

Unassisted Penché (°)

Significant at p < 0.05

5.69 ± 2.08

4.79 ± 2.50

Arabesque to Pass´e (reps)

*

1.85 ± 0.66

1.36 ± 0.26

Side-kick (s)

Dynamic balance tests

139.37 ± 19.74

124.88 ± 18.89

Unassisted front-split (°)

Active flexibility tests

0.003*

0.003*

0.000*

0.000*

0.000*

4.55 ± 1.97

1.34 ± 0.13

149.30 ± 18.47

148.54 ± 17.46

126.90 ± 19.74

Pre-test

5.68 ± 1.38

1.98 ± 0.89

163.32 ± 12.50

158.63 ± 15.27

139.27 ± 19.33

Post-test

(n = 11)

Pre-test

p value

(n = 21)

Post-test

Barre Training Group (BTG)

Whole Sample

Table 3 Pre-test and post-test result for the BTG and CTG (mean ± SD)

0.016*

0.033*

0.004*

0.005*

0.009*

p value

5.05 ± 3.07

1.42 ± 0.37

152.74 ± 15.72

143.39 ± 17.99

122.67 ± 18.71

Pre-test

(n = 10)

5.70 ± 2.74

1.76 ± 0.23

162.14 ± 14.86

154.70 ± 16.29

139.47 ± 21.24

Post-test

Center Training Group (CTG)

0.384

0.061

0.018*

0.022*

0.006*

p value

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Table 4 Percentage of improvement and significance level between experimental groups after 6 weeks barre and center training intervention Improvement (%) Whole Sample

p value Barre Training Group (BTG)

Center Training Group (CTG)

Active flexibility tests Unassisted front-split

11.60

9.75

13.70

0.466

Unassisted side-split

7.30

6.79

7.89

0.770

Unassisted Penché

7.83

9.31

6.15

0.364

Side-kick

36.03

47.76

23.94

0.280

Arabesque to Pass´e

18.79

24.84

12.87

0.383

Dynamic balance tests

*

Significant at p < 0.05

dynamic balance in both frontal and sagittal planes. Most previous studies reported improvement after ballet intervention among Latin dancers (Liu 2019) and cheerleaders (Liow 2019). It has been suggested that ballet does not allow many opportunities for resting any part of the body during practice (Ekegren et al. 2014) and possibly induces consistent recruitment of greater motor units to allow gymnasts to use their muscles more effectively while stabilizing their body when lifting legs that are in motion (Sawers et al. 2015). Ballet exercises such as the plié and développé exercises required controlled coordinated motion of both legs that could train core and pelvic stability (Sawers et al. 2015), while the grand battement trained the gymnasts to maintain or regain a stable position after overcoming the momentum gained during leg kicking at a quick pace, contributing to better dynamic balance. Unlike for active flexibility, BTG demonstrated a significant improvement in both dynamic balance tests, whereas no significant improvement was observed for CTG. The greater improvement observed in BTG may be due to the assistance of the barre which provided proprioceptive information that in turn contributed to better learning of motor control strategy, enabling the BTG gymnasts to gain better balance (Greenwell et al. 2020). In contrast, the removal of the barre the CTG contributed to a greater challenge in gaining stability when participants had to use their own muscular strength. This required higher technical precision imposed greater demands on the brain to activate muscle reflex synergies in the trunk and supporting leg just before the onset of leg lifting movements which could disrupt static balance for the participants (Wehmeyer and Weaver 2021). The current study was limited to young recreational level rhythmic gymnasts who obtained improvement due to additional training interventions above their usual technical training. Future research should consider experiences and elite level gymnasts to observe if similar training adaptations can be achieved. Another limiting factor was the short experimental duration. A longer experimental duration of 8 weeks has been suggested to be efficient for balance training protocols for athletic populations (Brachman et al. 2017). Future studies may also look into complex and advanced

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sport-specific skills including jumps and pirouette which are more correlated with gymnasts’ difficulty (D) score. The artistry and aesthetic aspect could be emphasized to examine the effectiveness of ballet training on rhythmic gymnasts’ execution (E) score.

5 Conclusion The findings of the present study suggest that ballet training seems to be an appropriate supplementary training modality that can enhance rhythmic gymnasts’ sportspecific qualities such as lower-limb active flexibility and dynamic balance. Ballet training could be utilized for specific physical preparation for rhythmic gymnasts and contribute to their development during early stages of their training life. Sufficient time and attention should be allocated for both barre and center training to achieve greater muscle activation levels while promoting a better development of a wide variety of motor strategies. Acknowledgements The authors would like to address their deepest gratitude towards the participants and relevant parties for their willingness to cooperate for the success of the study. Funding This research did not receive any specific grant or financial assistance from funding agencies in the public, commercial or non-profit sectors. Ethics Approval This study was approved by Faculty of Applied Science (FOAS) Research Ethics Committee of Tunku Abdul Rahman University College (TARUC).

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Pluemthanom A, Hurunrat S, Limroongreungrat W (2015) Three-dimensional analysis of balance control during basic rotation in rhythmic gymnastics. J Sports Sci Technol 15(1):27–34 Ren YE (2013) Classical ballet training system applied in artistic gymnastics training. Master’s Degree Thesis. Shanxi University Sands WA, McNeal JR, Penitente G, Murray SR, Nassar L, Jemni M, Mizuguchi S, Stone MH (2016) Stretching the spines of gymnasts: a review. Sports Med 46:315–327. https://doi.org/10. 1007/S40279-015-0424-6 Sawers A, Allen JL, Ting LH (2015) Long-term training modifies the modular structure and organization of walking balance control. J Neurophysiol 114(6):3359–3373. https://doi.org/10.1152/ Jn.00758.2015 Sheng J (2021) An experimental study on the integration of ballet basic training in college dance cheerleading teaching from the perspective of aesthetic education. Master Thesis. Central China Normal University. https://doi.org/10.27159/D.Cnki.Ghzsu.2020.001723 Sherman AJ, Mayall E, Tasker SL (2014) Can a prescribed turnout conditioning program reduce the differential between passive and active turnout in pre-professional dancers? J Dance Med Sci off Publ Int Assoc Dance Med Sci 18(4):159–168. https://doi.org/10.12678/1089-313X.18. 4.159 Sobera M, Rutkowska-Kucharska A (2019) Postural control in female rhythmic gymnasts in selected balance exercises: a study of two cases. Polish J Sport Tour 26(1):3–7. https://doi.org/10.2478/ Pjst-2019-0001 Van Camp J (2015) A rationale for a ballet exercise-based balance training programme for older adults with balance impairments: an alternative approach to a group- based balance training in physiotherapy. Bachelor’s Thesis. Tampere University Of Applied Sciences Vieira De Jesus DS (2013) Réquiem Para Dois Pássaros De Gelo: A Coreografia Da Exclusão Na Patinação Artística Soviética E A Construção Da Potência Esportiva Mundial. Rev Estud Fem 21(3):1211–1230. https://doi.org/10.1590/S0104-026X2013000300024 Wang J (2020) Study on the influence of ballet basic training on the artistic expression of synchronized swimmers. Master Degree’s Thesis. Guangzhou Sport University Wehmeyer M, Weaver C (2021) The effect of a traditional ballet barre versus a modified ballet barre on flexibility, ankle stability, and abdominal strength & endurance in collegiate dancers. Undergraduate Research Scholars Thesis. Texas A&M University Wilmerding V, Krasnow D (2011) Dance pedagogy: myth versus Reality. In: Williamson A, Edwards D, Bartel L (eds) Proceedings of the international symposium on performance science 2011. Utrecht, The Netherlands: European Association Of Conservatoires, pp 283–289 Zhang RY (2020) Experimental research on the influence of basic ballet training on ankle stability of college ballroom dancers. Undergraduate Research Scholars Thesis. Hunan Normal University Zhou YN (2020) Experimental study on ballet body training in dance cheerleading. Master’s Degree Thesis. Shanxi University

The Effect of Short-Duration Resistance Training Voluntary to Failure on Muscle Adaptation of Men in Overweight Nur Dania Rosaini, Siti Syahirah Aqilah Shafee, Al-Hafiz Abu Bakar, Norazwan Mokhtar, Harris Kamal Kamaruddin, and Ahmad Dzulkarnain Ismail Abstract The increments in the prevalence of the overweight population are alarming as the high level of body weight and adiposity are often associated with an increased risk of developing numerous health complications. Most adults did not engage in regular physical activity due to reasons such as time constraints. Therefore, this study aimed to investigate the effects of short-duration resistance training to voluntary failure for three weeks on muscle strength adaptations. Ten overweight men (age 23 ± 4 years; height 171.6 ± 4.7 cm; weight 80.6 ± 5.8 kg; body mass index (BMI) 27.4 ± 1.2 kg m−2 ) were recruited for this study. The resistance exercise training involved one session per week for three weeks. Each training session involved three sets of eight exercises, performed at 80% of 1-RM to voluntary failure and lasted about 30 min. Muscle strength test was performed at baseline and postintervention using 1-RM protocol. Muscle mass and body adiposity measurements were taken at baseline, each week after the training session and after the intervention. At the end of the intervention, muscles strength and mass increased by 6.9% and 0.4%, respectively, from baseline. The body adiposity decreased by 0.4% after the intervention. In conclusion, once-weekly of resistance training voluntary to failure for three weeks resulted in improvement in muscle strength and mass, and reduction in body adiposity in men with excess weight. Keywords Muscle adaptations · Muscle mass · Overweight men · Resistance training · Voluntary to failure N. D. Rosaini · S. S. A. Shafee · A.-H. A. Bakar · N. Mokhtar · H. K. Kamaruddin · A. D. Ismail (B) Faculty of Sports Science and Recreation, Universiti Teknologi MARA Perlis, 02600 Arau, Perlis, Malaysia e-mail: [email protected] A.-H. A. Bakar e-mail: [email protected] N. Mokhtar e-mail: [email protected] H. K. Kamaruddin e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_24

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1 Introduction Over the years, the prevalence of the population being overweight continues to increase. Overweight is defined as an individual who has a body mass index (BMI) greater than or equal to 25 kg m−2 (Nuttall FQ 2015). According to the National Health and Morbidity Survey (2019), it is reported that the prevalence of adults that are overweight has reached 30.4%. The age group that showed the highest level of overweight individuals is adults aged 55–59 years old (National Health and Morbidity Survey 2019). Condition is alarming as the high levels of body weight and adiposity are often associated with an increased risk of development of health issues (Billington et al. 2000; Field et al. 2001). Being overweight is a predictor that a person may have cardiovascular atherosclerosis (Billington et al. 2000; Field et al. 2001; Manson et al. 1990) and also increase the risk of getting ischemic stroke (Billington et al. 2000; Field et al. 2001). It is proven that a person that has a BMI of 25 kg m−2 or greater has a higher risk of attaining noncommunicable diseases such as cardiovascular and metabolic diseases through being overweight. In Malaysia, the highest level of overweight individuals can be seen among adults aged 55–59 years old (National Health and Morbidity Survey 2019). It was reported that Malay and Indians have a higher risk of being overweight, obese, or having type 2 diabetes (Boo et al. 2010; Khambalia and Seen 2010; Moy and Bulgiba 2011; Sidik and Rampal 2009; Wan Mohamud et al. 2011). This issue is closely associated with a lack of physical activity (Wellman and Friedberg 2002). Most adults did not engage in physical activity due to reasons such as time constraints (Petrin et al. 2017; Pojednic et al. 2017). Having low muscle strength is associated with a higher risk of getting health problems such as cardiovascular disease, respiratory disease, and cancer (Celis-Morales et al. 2018). Resistance training is closely associated with muscular hypertrophy and strength gain (Mangine et al. 2015). The benefits of resistance training such as reducing cardiovascular risk factors, improving glucose and lipids metabolism (Ashton et al. 2020; Hills et al. 2010; Strasser and Pesta 2013), and also improving the insulin sensitivity especially among overweight men (Ismail et al. 2019). It is important to participate in resistance training for muscle strength and mass gain to lessen the risk of developing health problems (Ashton et al. 2020). The American College of Sports Medicine (2013) recommendation for resistance training is two to three days per week. However, there are different recommendations for individuals with overweight and obesity. It is recommended for them to participate five days or more per week with moderate to vigorous intensity to maximize caloric expenditure. The resistance training is the high-intensity exercises against resistance, to strengthen and build lean muscle. In the study by Willis et al. (2012), a training program that includes resistance training is crucial for increasing lean mass among overweight individuals. In the study by Cote et al. (1988) and Vissing et al. (2008), certain resistance training routines employed a high degree of muscle tension that allows the inducing of neural adaptation. The duration of six weeks of resistance training has been proven

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effective to improve muscle strength and quality (Scanlon et al. 2014). In the study by Mangine et al. (2015), high-intensity resistance training contributed to a greater increment of strength and hypertrophy in a short-term training period. It is also shown that training to failure will enhance exercise-induced metabolic stress which will allow a greater chance for hypertrophic response (Schoenfeld 2010). In a recent study by Ismail et al. (2019), it is proven that single-set resistance training to voluntary failure for six weeks resulted in a positive adaptation to muscle strength and mass gain among overweight men. In the study, three sessions of shortduration resistance training per week for six weeks was proven to be effective to improve muscle strength. However, it remains to be established whether one session of short-duration resistance training for three weeks can also produce similar muscle adaptations. The aim of the present study, therefore, was to investigate the effects of one session of short-duration resistance training for three weeks, consisting of three sets of each exercise to voluntary failure on muscle strength, muscle mass, and body adiposity in overweight men.

2 Methods 2.1 Ethical Approval Participants provided with written informed consent, and the study was approved by the Research Ethic Committee of Universiti Teknologi MARA, REC/12/2021 (UG/MR/1027) and adhered to the ICH Good Clinical Practice Guidelines, Malaysia Good Clinical Practice Guidelines and the Declaration of Helsinki.

2.2 Participants The sample size calculation (Dupont and Plummer 1998) revealed that 10 participants would allow detection of a significant difference of 1% in body adiposity mass (Ismail et al. 2019) with the statistical power of 1 − β = 0.80 and α = 0.05. The participants were recruited among the students and staff from Universiti Teknologi MARA, Cawangan Perlis, Kampus Arau. Ten overweight men (age 23 ± 4 years; height 171.6 ± 4.7 cm; weight 80.6 ± 5.8 kg; body mass index 27.4 ± 1.2 kg m−2 ) were recruited for this study. Mean body mass index (BMI) ranging from 25 kg m−2 to 29.9 kg m−2 , free from injuries, metabolic, and cardiovascular diseases, has the blood pressure below 140/90 mmHg and does not participate in moderate-high intensity aerobic exercises and resistance training in the past two years.

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2.3 Study Protocol Participants were required to attend a baseline visit. During the baseline visit, the participants’ body composition which are the body mass, height, BMI, muscle mass, body adiposity, and 1-RM measurements was taken by the researcher. The height of the participants was measured in cm using a stadiometer (SECA, German), and the bodyweight was taken using a digital weighing scale (SECA, German). The participants were required to remove their shoes and empty their pockets for any additional weights so that the measure can be taken as accurately as possible. From the height and body weight obtained, the body mass index was calculated using the BMI formula (BMI = Weight (kg)/Height2 (m). The measurements of 1-RM were used to estimate the intensity during the three weeks training program. The participants were briefed about the objective of the study, obtained the PAR-Q, a consent form to participate, and familiarization with the experimental protocols. The participants’ body adiposity and muscle mass were measured using a body composition analyzer (TANITA BC-418, Tokyo, Japan) according to the manufacturer’s guidelines. The participants were required to remove their shoes and empty their pockets for any additional weights so that the measure can be taken as accurately as possible. The participants’ 1-RM strength test was tested using eight exercises which consist of leg press, leg extension, calf press, chest press, seated row, lat pulldown, bicep curl, and tricep curl using the strength training machine using a protocol adapted from Ismail et al. (2019).

2.4 Resistance Training Intervention The 1-RM Strength Test was performed at the baseline and post-intervention. The participants completed each of the eight exercises to the maximal weight that they can lift in one repetition. Before starting the 1-RM Strength Test, the participants performed a standardized warm-up. With the instruction from the investigator, the participants begin the 1-RM Strength Test. The same investigator recorded the 1-RM measurement during the baseline visit and the post-intervention. After getting the baseline data, the resistance training intervention was conducted for three weeks at gymnasium at Universiti Teknologi MARA, Cawangan Perlis, Kampus Arau. The resistance training intervention consisted of one training session per week, where the participants performed three sets of the eight exercises at 80% of 1-RM to voluntary failure. The participants performed by using the strength training machine (Cybex, United States of America). Each week, the resistance training session was conducted on Monday morning. The duration of the training sessions was 45 min. Each week, the participants came two times: the first day for resistance training and the next day for body composition measurement. At the end of the three weeks intervention, the post-intervention data were collected three days later.

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2.5 Data Analysis All the data is presented as mean ± standard deviation (mean ± SD). All data obtained in this research was analysed using the Statistical Package for the IBM SPSS v26 2016. The time-course data for the weekly muscle mass and body adiposity were compared over time via a Wilk’s Lambda. The significance is set at p ≤ 0.05.

3 Results Table 2 shows the changes in the mean values of muscle strength pre- and postintervention. The 1-RM for all eight exercises showed significant differences between the baseline and post-intervention measurements (p < 0.05). Overall, the sum of the individuals 1-RMs for all eight exercises was 6.9% higher after the intervention when compared with the baseline values (Table 2). A significant main effect on the time course data for the weekly muscle mass overtime was obtained; Wilk’s Lambda = 0.068, F (4, 6) = 20.645, p < 0.001, Table 1 Schematic representation of the experimental protocol Muscle mass Body fat 1-RM

Baseline √

Week 1 √

Week 2 √

Week 3 √

Post √

√

√

√

√

√

√

√

Table 2 One-repetition maximum for training exercises before and after three weeks of resistance training intervention Variables

Baseline (kg)

Post-intervention (kg)

Leg PRESS 1RM

Percentage increase (%)

173.5 ± 40.7

201.1 ± 46.7

6.3

Leg Extension 1RM

47.0 ± 11.8

65.1 ± 16.9

12.1

Calf press 1RM

81.2 ± 26.5

109.3 ± 41.0

18.8

Chest press 1RM

34.7 ± 10.4

41.7 ± 10.9

15.4

Seated row 1RM

11.8 ± 1.9

14.3 ± 2.7

11.2

8.4 ± 1.8

9.8 ± 1.7

10.1

Bicep curl 1RM

12.5 ± 4.6

22.2 ± 7.9

8.6

Triceps curl 1RM

35.7 ± 10.3

43.1 ± 8.1

27.8

404.2 ± 90.2

506.7 ± 119.3

6.9

Muscle mass (kg)

38.0 ± 7.5

39.5 ± 7.3

0.4

Body adiposity (%)

32.6 ± 2.8

31.2 ± 2.6

0.4

Lat pull down 1RM

Sum of individual 1-RMs

Data are means ± SD

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Fig. 1 Total muscle mass time-course of adaptations in response to three weeks of resistance training voluntary to failure intervention. Data are presented as means ± SD

partial eta squared = 0.932 (large effect size) shows that there was a significant increment in participants’ muscle mass across the resistance training intervention (Fig. 1). The mean muscle mass during the baseline was 38.0 ± 7.5 kg. After the three weeks of resistance training intervention, the mean muscle mass during the post-intervention increased to 39.5 ± 7.3 kg. Results show 0.4% improvement in muscle mass. A significant main effect on the time course data for the weekly body adiposity overtime was obtained; Wilk’s Lambda = 0.01, F (4, 6) = 147.678, p < 0.001, partial eta squared = 0.990 (large effect size) shows that there was a significant decrement in participants’ body adiposity across the resistance training intervention (Fig. 2). The mean body adiposity during the baseline was 32.6 ± 2.8 kg. After the three weeks of resistance training intervention, the mean body adiposity during the postintervention reduced to 31.2 ± 2.6 kg. The body adiposity shows 0.4% decrement after three weeks of resistance training intervention.

4 Discussion The present study has shown that three weeks of one session resistance training, consisting of three sets of eight exercises to voluntary failure resulted in an increment of 0.4% in muscle mass in healthy overweight men. Apart from that, increment in muscle strength and reduction in body adiposity were also observed in this study. While the previous study has demonstrated that single set resistance training to

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Fig. 2 Total body adiposity time-course of adaptations in response to three weeks of resistance training voluntary to failure intervention. Data are presented as means ± SD

voluntary failure for three times per week can increase muscle strength (Ismail et al. 2019; Mitchell et al. 2012), the present study is the first study to demonstrate that doing three sets of the eight exercises for one session per week, with time allocation for each session is less than 1 h, can also produce similar adaptation in muscle strength, muscle mass, and body adiposity. The previous study has shown that a short period of resistance training has several benefits such as reducing cardiovascular risk, improving glucose and lipids metabolism (Ashton et al. 2020; Hills et al. 2010; Strasser and Pesta 2013), and also improving the insulin sensitivity among overweight men (Ismail et al. 2019). The American College of Sports Medicine (2013) suggested that the overweight and obese population are encouraged to participate in resistance training for five days or more per week with moderate to vigorous intensity to maximize caloric expenditure. However, several studies mentioned that one of the reasons for physical inactivity or lack in exercising is time constraints (Petrin et al. 2017; Pojednic et al. 2017). This shows how duration has become one of the factors that influence participation in exercise. Being physically inactive will cause weight gain, loss of muscle mass, and bone density (Shiroma et al. 2017). Having low muscle strength is associated with a higher risk of getting health problems such as cardiovascular disease, respiratory disease, and cancer (Celis-Morales et al. 2018). Therefore, this study has been able to show that doing only one session of short-duration resistance training to voluntary failure was able to increase the strength of the muscle (p < 0.05). The previous study by Ismail et al. (2019) mentioned that doing a single set of resistance training to voluntary failure three times per week is effective to increase muscle strength and size. Mitchell

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et al. (2012) have also agreed with single-set resistance training to voluntary failure can increase the strength of the muscle. Since time commitment for the single set of resistance training by Ismail et al. (2019) was less than 1 h for each training session, this study aimed to see the adaptations to the muscle when the training is performed one session per week. As the study by Ismail et al. (2019) was focused on doing a single set for three sessions per week, this study was able to show that doing three sets for one session per week could also produce similar adaptations to the muscle mass and strength. The duration for the one session per week was in 45 min; thus, it can be suitable for overweight people to commit to the training when time constraint was one of their challenges in participation in physical activity (Petrin et al. 2017; Pojednic et al. 2017). On the other hand, the outbreak of COVID-19 in Malaysia since January 25, 2020, has caused some changes in physical activity participation among Malaysians. The implementation of the Movement Control Order (MCO) on the March 18, 2020, has restricted Malaysian to go out in public places unless it is necessary (Elengoe 2020). Although now the MCO has been lifted and 97.9% of Malaysian adults have been fully vaccinated as of February 6, 2022 (COVIDNOW 2022), the preventative method has still been taken to avoid getting the transmission of COVID-19. Since COVID-19 can be transmitted through the droplets from coughing and sneezing and also close contact with an infected person (Elengoe 2020), it is advised to maintain a physical distancing of one meter and spending less time in closed space. Since a gym or fitness center is usually packed with people, some people avoid going to the gym altogether thus it might lead to physical inactivity. However, this study has provided a new way of resistance training where people could gain muscular adaptations and maintained their physical activity level even by only going to the gym once per week and spending less time in the gym as each session is less than one hour. Apart from that, going to the gym once per week and performing 80% of 1-RM to voluntary failure for three sets can also be cost-effective in terms of vehicle petrol and gym membership as it provided the same result as training three or four times per week. As high levels of body adiposity could lead to an increased risk of developing health complications such as atherosclerosis and ischemic stroke especially among the overweight and obese population, this study has proven that doing only one session of resistance training to voluntary failure per week can help to reduce the body adiposity. Over three weeks, the body adiposity can be reduced by 1.4%. Apart from that, this resistance training intervention does not involve a rigid dietary program that needed to be followed by the participants. When compared with a previous study by Ismail et al. (2019), this study has added the data on the adaptations to the muscle when comparing a single set of resistance training three times per week and three sets of resistance training for one time per week. Since this study has combined all the sets into one training session, it can benefit those who have a work commitment to still engage in resistance training. Furthermore, this training consists of high intensity to voluntary failure for one session per week allow sufficient recovery time for the participants.

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Doing high-intensity resistance training which encompasses 80% and above of 1RM can produce more strength gain than low-intensity resistance training (Mitchell et al. 2012). It is shown that higher intensity produces greater muscular adaptation such as muscle hypertrophy (Campos et al. 2002; Holm et al. 2008; Schuenke et al. 2012) due to the exercise-induced stress that has acted upon the muscle (Evans 2002; Jones and Rutherford 1987; Vandenburgh 1987). The training volume must match sufficiently when training at the different intensities to gain the maximal responses from the training (Lasevicius et al. 2018). It was proven by several studies on how the volume of training is more important than the frequency of the training to see the hypertrophic and strength gained in response to the training. (Colquhoun et al. 2018; Peterson et al. 2004; Rhea et al. 2002; Robbins et al. 2012; Rønnestad et al. 2007). Although the frequency of the resistance training for this study is lower, whereby the training is only performed once per week, the training volume is higher resulting from the three sets to voluntary failure. It is also proven by the previous study that short-duration high intensity training will produce greater improvement in muscular hypertrophy and strength (Mangine et al. 2015; Mitchell et al. 2012). The stress induced from performing the exercise to voluntary failure generates greater muscular contraction (Jessee et al. 2018). The effectiveness of performing resistance training to voluntary failure for hypertrophic response and strength gain has been proven in the previous study by Ismail et al. (2019) and Dankel et al. (2016). Although the resistance training intervention in this study contradicted with the recommendation from the American College of Sports Medicine whereby normal population should perform two to three days of resistance training per week and overweight and obese population should participate five days or more in resistance training, this study can produce positive adaptation to the muscle. These adaptations could reduce the health complication risk that is faced by the overweight population. Furthermore, the resistance training method in this study can help the overweight population to start joining the resistance training program without feeling overwhelmed to go to the gym multiple times per week and reduced the risk of disengagement from the resistance training program. The present data add to the evidence-based on muscular adaptations on resistance training for three weeks. From this, the adaptations can be seen and compared with the data of resistance training that was performed for 6 weeks, 12 weeks, and more than 24 weeks. Since the result from this study can be seen as early as three weeks of doing high intensity, short-duration resistance training to voluntary failure, it will make the participants more motivated to keep participating in the training. The adjustment of the training load after the three weeks mark will allow for much greater improvement in muscle strength, muscle mass, and body adiposity as demonstrated in the previous study by Ismail et al. (2019). Participating in this method of resistance training can be predicted to produce a greater muscular adaptation in a long run. However, this study possessed several limitations to it. The selection of participants among the overweight population may only demonstrate the benefits from these exercises to the overweight population. Since this study only focuses on overweight men, it is yet to be established the muscular adaptations to overweight women when undergoing the one session short-duration resistance training to voluntary failure at

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80% of 1-RM. Moreover, this study does not focus on following a specific dietary plan and was not focused on the weight loss program.

5 Conclusion In conclusion, the present study shows that one session of short-duration resistance training to voluntary failure performed at 80% of 1-RM for three sets for three weeks results in the increment of muscle strength (6.9%) and muscle mass (0.4%) while simultaneously reducing the body adiposity (0.4%) in overweight men. The finding of this study opens up for a new way of resistance training intervention by performing it once per week rather than multiple times per week to improve the muscle and metabolic health of the overweight population. These findings require further investigation. Acknowledgements The authors would like to thank Faculty of Sports Science and Recreation, UiTM Perlis Branch who gave us support and courage to do this wonderful project on the topic. Thank you, Research Management Centre (RMC), of UiTM for funding this research by giving Young Talent Researcher (YTRK) Grant.

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Understanding Emotional Intelligence and Personality to Athletes’ Performances: a Systematic Literature Nur Afifah Saufi, Ahmad Fikri Mohd Kassim, and Siti Hannariah Mansor

Abstract Emotional intelligence is a set of personal characteristics that expresses intelligence’s adaptability and subjective emotional experiences. Emotional intelligence is a potent feature that contributes to the development of logical, selfexpression, and social behavior patterns in healthy persons. Personality, on the other hand, is defined by human ideas, feelings, and behaviors and seeks to define a person. Personality considers both generic characteristics as well as individual distinctions. As a result, the goal of this study is to comprehensively analyze the existing literature on the emotional intelligence and personality of young athletes. This study included an intensive online review of the data source (Scopus and Web of Science) as well as a conference of potentially related papers referring to PRISMA protocols. The search methods were limited to studies that had full-text access and were published in English. In the search engines, the terms emotional intelligence, emotional perceptions, personality, and attributes were evaluated. A total of 23 studies were selected from a total of 52 records, with dates ranging from 2015 to 2021. However, only a few papers made it through the screening, with nineteen being chosen for qualitative synthesis and four for quantitative synthesis. The findings examine crosssectional observational research on emotional intelligence and personality in depth. It is feasible to investigate emotional intelligence and personality further when both components are engaged. Emotion is linked to a person’s internal processes and can be used to motivate them to participate in activities, especially for young athletes. Keywords Emotional intelligence · Personality · Youth athletes · Systematic review

N. A. Saufi · A. F. Mohd Kassim (B) · S. H. Mansor Faculty of Sports Science And Recreation, Universiti Teknologi Mara, Perlis Branch, Arau Campus, 02600 Arau, Perlis, Malaysia e-mail: ahmadfi[email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_25

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1 Introduction Every professional sector suffers a high societal weight because of society’s many issues. Emotional stress, feelings of inadequacy, a loss of hope, and a lack of appreciation are common in these people. The concept of “feeling” is one of the most critical difficulties to overcome before establishing emotional intelligence. Emotions, like human biology, have various purposes and so exist throughout a person’s development. More broadly, Goleman (Galea and Lindell 2016) defines emotional intelligence as the ability to mobilize oneself, progress without giving up in the face of adversity, to ay gratification by controlling motives, maintain a balanced mental state, avoid allowing problems to impair one’s ability to think, to understand another person’s feelings and thoughts, and to think optimistically. In contrast to cognitive intelligence, which is innate, emotional intelligence can be cultivated through time by increased awareness of education, experience, and emotions (Balyan et al. 2021). Emotional intelligence, according to Goleman (1995), is defined as the ability to control and regulate one’s feelings, understand other people’s feelings, and use emotions as a guide for actions and thought. Emotional intelligence can be describe as the capacity to recognize, express, comprehend, motivate, control, and regulate emotion. Emotional intelligence people are self-aware, capable of controlling their emotions in the face of extreme stress, despair, anxiety, or wrath, and can postpone their enjoyment in favor of long-term goals rather than being overwhelmed by immediate demands (Piepiora 2021; Mayer et al. 2016). Many emotional intelligence and sports practice methods share the trait of being extremely practical, especially in terms of application in daily life. Emotional intelligence may helps athletes make better decisions, remember things, think more clearly, and solve problems. Emotional intelligence could also be linked to stress management or an athlete’s own desire to exercise, which could indirectly contribute to personality changes. From times to the present, one of the most fascinating qualities of human people has always been their personality. Personality refers to the characteristics and practices that distinguish one individual from the others. Individual, relationship, group, and societal outcomes are all predicted by personality traits. Beyond defining individual differences, a thorough grasp of personality processes explains how those differences manifest themselves. Emotions and motivations, social styles, selfawareness, and self-control are all characteristics of the human personality that play a role in behavioral consistency (Linden et al. 2012). However, because the personality qualities of athletes greatly influence personality types, it is difficult to separate and define the most appropriate personality type (Petrides et al. 2016). As a result, it’s safe to conclude that students’ athletes place high importance on their academic performance and overall college experience. The development of academic talents in students’ athletes necessitates adequate psychological and psycho-physical health. Its goal is to pique students’ athletes interest in continuing to learn throughout their lives and to encourage self-improvement in both professional and personal areas.

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2 Method Search strategy: A systematic review seeks to discover, search, and synthesize relevant literature in an organized and transparent manner, utilizing repeatable techniques at each step. Systematic reviews are sometimes known as meta-narrative reviews (Piepiora 2021). This method enables a single review of several study designs (qualitative and quantitative). Studies of various designs and concepts can be reviewed (Piepiora 2021). It also validates the researchers’ claims and helps identify gaps, trends, and future study areas. Selected databases (Scopus and Web of Science) were utilized to search for information using the RAMESES approach (identification and screening process). RAMESES: A Realist and Meta-narrative Evidence Synthesis: Evolving Standards (RAMESES) guideline was adopted by the writers (Piepiora 2021). This strategy proposes including essential elements like abstract, introduction, methods, results, and discussion sections, with specifics in each (review process, search process, and document selection). RAMESES is suitable for social science systematic reviews since it (1) explicitly states the research questions, (2) identifies criteria (inclusion and exclusion), and (3) aims to analyze major scientific databases within a given time. Resources: This review employed Scopus and Web of Science, two major indexed databases (WoS). Both databases are considered top citation indexing systems. WoS is a scientific citation indexing service available solely through institutional subscriptions, while Scopus covers a wide range of subject areas and document types including scientific journals, books, and conference proceedings. Track, analyze, and visualize research with Scopus. These two indexed databases were chosen for their fame, which ensures the quality of the papers examined in this paper. Systematic review process (Identification): The systematic review begins with identification in July 2021. The data screening was reviewed by the authors before proceeding to the next step. The method involved identifying keywords for information searches. Keywords from prior literature and keywords provided by Scopus for keyword synonyms, probably related terms, and other variations to the term rural.

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Table 1 Inclusion and exclusion criteria Criteria

Inclusion

Exclusion

Timeline

Between 2015 and 2020

0.05) • In fact, EI becomes even more relevant when we have to work in teams where we cannot choose their members or when our business duties force us to work and interact with people with very heterogeneous personalities • Developing the ability to manage emotions and filter stressful stimuli is of utmost importance for students immediately in the school context, but also in the future in their professional context • A correlation between students’ EI and their academic performance. It is not possible to directly infer a relationship between academic performance and a go performance in the seat game, but it is possible to explore the use of serious games in the development of emotional skills that, along the academic and professional path of students, may be important for their career

(continued)

2019, article journal, English, quantitative and qualitative

Adoption of a Serious Game in the Developing of Emotional Intelligence Skills (2019) Fernando Almeida

5

• Triangulation design approach • Master Analytics Profiler (MAP)

• A descriptive, correlational • Between the students’ average scores on the ICS-A-total 2018, article study Nurse’s and subscale item scores and their average scores on journal, English, • The Nurses’ Professional Values the Emotional Intelligence Evaluation Scale, there was a qualitative Scale-Revised (NPVS-R) strong significant correlation (r = 0.574) (p < 0.001). The • Emotional Intelligence averages of the NPVS-R total and factor scores and the Evaluation Scale averages of the Emotional Intelligence Evaluation Scale total • Individualized Care Scale and certain subscale scores of the students who participated in A-Nurse Version (ICS-A-Nurse) the study had a significant positive correlation (r = 0.444) (p < 0.001) • Nurses with advanced emotional intelligence skills can meet the emotional needs of the individual by directing the feelings of both themselves and the individuals they help during care practices and can set an individualized care relationship by becoming aware of the emotions and thoughts that make the individual more privileged than others

• 375 nurses

The relationship between student nurses’ values, emotional intelligence and individualized care perceptions (2018) Yeliz Culha & Rengin Acaroglu

Inclusion reason(s), pub year, pub type, language, study design

4

Outcome/conclusion

Study design

No. Journal name, authors, publication Number of year participants, participants

Table 2 (continued)

312 N. A. Saufi et al.

Emotional Self-Regulation through Introjective Practices in Physical Education (2020) Dolors Cañabate, Mónica Santos, David Rodríguez, Teresa Serra & Jordi Colomer

7

• 90 fourth-year primary school students

• Trait Meta-Mood Scale (TMMS)

• A descriptive, correlational study • The self-regulation questionnaire • The “My Life as a Student” questionnaire • The Emotional Intelligence Scale (EIS) • The Smartphone Addiction Scale (SAS)

Emotional Intelligence, Self-Regulation, Smartphone Addiction: Which Relationship with Student Well-Being and Quality of Life? (2020) Maria Lidia Mascia, Mirian Agus & Maria Pietronilla Penna

6

• 215 students

Study design

No. Journal name, authors, publication Number of year participants, participants

Table 2 (continued) Inclusion reason(s), pub year, pub type, language, study design

• For the analysis of gender during the application of the treatments, there were significant gender differences between the pre-test and the post-test (p < 0.01). There was no statistically significant (p > 0.01) interaction between the treatments and the gender component • The significant differences between the pre-and post-tests, as well as our observations of the approach, showed that the practice of mindfulness in educational practice helps students to identify and become aware of the emotions they feel, with this being the first crucial step toward being able to manage their emotional states. Children first learn to identify their emotions by becoming aware of the present moment and, as a result, they gradually acquire the skills that enable them to have greater self-control • Girl students were highly aware of their emotional states, and these improved following the approach • The findings indicated that emotional perception, emotional comprehension on a deep level, and emotional regulation all served to balance the intake of emotional skills

(continued)

2020, article journal, English, quantitative

• Self-control and emotional intelligence specifically have 2020, article beneficial effects on well-being reported (p < 0.001) journal, English, • Findings confirm the positive effect of self-regulation and quantitative emotional intelligence on well-being • It was also emphasized how self-control harms smartphone addiction. The connection between well-being, smartphone addiction, and indirect impacts on self-regulation has not yet been proven. To achieve psychological and social well-being and, subsequently, overall life satisfaction, emphasis should be made on education about emotional intelligence and self-regulation

Outcome/conclusion

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Emotional Intelligence and Academic Achievement in Higher Education (2020) Florentina Halimi, Iqbal AlShammari & Cristina Navarro

9

• 480 Kuwaiti college students

• Wong and Law Emotional Intelligence Scale (WLEIS)

• Descriptive correlational, cross-sectional study • Abbreviated Self-Leadership Questionnaire (ASLQ) • Wong’s Emotional Intelligence Scale (WEIS)

The Relationship between Self-Leadership and Emotional Intelligence among Staff Nurses (2019) Eman Alabdulbaqi, Hasnah Banjar & Ohood Felemban

8

• 158 registered nurses

Study design

No. Journal name, authors, publication Number of year participants, participants

Table 2 (continued) Inclusion reason(s), pub year, pub type, language, study design

(continued)

• Find a significant correlation between EI and academic success 2020, article in two dimensions (SEA and UEO), but not in the overall scale journal, English, • Males’ total EI scores were higher than those of females (p ≤ quantitative 0.05) • No significant differences between the school sector on EI • Find a significant relationship between GPA and overall EI level, EI skills appear to be important predictors of academic success: the greater the EI, the higher the academic achievement • The results of the current study support research suggesting that curricula designed to increase students’ EI could assist educators in the classrooms by helping their students reach successful academic performance

• Emotional intelligence and self-leadership had a statistically 2019, article significant positive correlation (p-value 0.016). In other words, journal, English, there is a statistically significant correlation between quantitative emotional intelligence and self-leadership • Expressing emotions at work is a lack of professionalism in which they used to ignore their emotions and exercise more self-leadership • Self-leadership is positively related to emotional intelligence, which means that the highest self-leadership level will lead to the highest emotional intelligence and vice versa

Outcome/conclusion

314 N. A. Saufi et al.

• Descriptive quantitative methodology • Psychometric properties of IED • Big Five Questionnaire

• 143 dancers

10

Emotional Intelligence of Spanish Dancers and Its Relationship with Personality Traits (2020) Rosa de las Heras Fernández, María Espada, Mª Virginia García Coll, Juana María Anguita

Study design

No. Journal name, authors, publication Number of year participants, participants

Table 2 (continued) Inclusion reason(s), pub year, pub type, language, study design

(continued)

• In addition, the findings of this research study enable us to 2020, article consider the work of emotional intelligence at early ages, journal, English, since given the results the age at which training begins quantitative influences enabling professionals to properly develop emotional intelligence, although currently there is a void in that respect at early ages of training. There are statistically significant variations between emotional self-regulation and the age at which individuals began dance training. F (4) = 2.940, p = 0.02 • Conscientiousness and responsibility (r = −0.313; p = 0.000), agreeableness (r = −0.453; p = 0.000), extraversion (r = −0.415; p = 0.000), and openness (r = −0.210; p = 0.013) all significantly and negatively connect with emotional hetero-regulation. Contrarily, emotional perception has a positive correlation with neuroticism (r = 0.179; p = 0.037) and a substantial negative correlation with conscientiousness and responsibility (r = −285; p = 0.001). Positive correlations between emotional self-regulation and agreeableness (r = −0.220; p = 0.009) and extraversion (r = −0.317; p = 0.000) have been found. Last but not least, emotional usage significantly and negatively correlates with responsibility and conscientiousness (r = −0.177; p = 0.035), as well as agreeableness (r = −0.210; p = 0.012) • Lastly, although our findings indicate that professional Spanish dance and flamenco dancers in Spain have high levels of competence in managing their emotions, specific knowledge of the different aspects of emotional intelligence related to personality could be very useful for directors and choreographers concerning dancers’ training and development

Outcome/conclusion

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Significance of Emotional Intelligence for The Innovative Higher School Teacher’s Readiness For A Person-Centered Interaction (2020) Asya Berberyan

Mood Responses and Regulation Strategies Used During COVID-19 Among Boxers and Coaches (2020) Reece J Roberts & Andrew M Lane

12

13

• 44 boxers

• 36 teachers

• BRUMS questionnaires • A qualitative analysis

• Hall’s questionnaire • Author’s methodology

• Emotional Intelligence Inventory • Self-designed survey

Medical Studies, Team Roles and Emotional Intelligence (2018) Maciej Walkiewicz, Katarzyna Sowi´nska & Małgorzata Tartas

11

• 200 students

Study design

No. Journal name, authors, publication Number of year participants, participants

Table 2 (continued) Inclusion reason(s), pub year, pub type, language, study design

• Results indicated significantly (p < 0.01) mood states changes before to during COVID-19 • To conclude, results suggest COVID-19 had a significant negative impact on boxers’ mood state, a profile that was significantly more unpleasantly if participants reported symptoms of depression • Boxers were affected by changes in training, a finding that suggests how closely boxing training plays in mood regulation

• Positive correlation between emotional intelligence and the innovative indicator of the ability for personality-centered interaction of higher school teachers • The key role in the development of modern society is facilitated by the readiness for person-centered interaction, which underlies the student’s creative development and potential, as well as indicators of the teacher’s humanistic orientation

(continued)

2020, article journal, English, quantitative & qualitative

• Medical students presented higher levels of individualism, 2018, article lower levels of emotional intelligence, as well as higher levels journal, English, of stress related to their studies, and higher satisfaction with quantitative the chosen studies. Nursing students were more focused on teamwork • No significant differences between the genders were found in terms of the level of stress or satisfaction reported (p > 0.05). The style of cooperation involving intellect and knowledge was negatively correlated with emotional intelligence • In comparison with nursing students, the research participants’ emotional intelligence scores were noticeably lower for the medical students

Outcome/conclusion

316 N. A. Saufi et al.

The Impact of Improving Emotional Intelligence Skills Training on Nursing Students’ Interpersonal Relationship Styles: A Quasi-experimental Study (2018) Orkun Erkayiran & Fatma Demirkiran

Do The Big Five Personality Traits Predict Individual Differences In The Left Cheek Bias For Emotion Perception? (2016) Samantha Galea & Annukka K. Lindell

15

16

• 74 participants

• 72 students

• NEO Personality Inventory • The Flinders Handedness Survey

• Emotional Quotient Inventory • Interpersonal Style Inventory

• Metacognitive Skills Data • Self-regulated Learning Perceptions Scale • Personal Information Form

Metacognition and Self-regulated Learning in Predicting University Students’ Academic Achievement in Turkey (2017) Baris Cetin

14

• 276 students

Study design

No. Journal name, authors, publication Number of year participants, participants

Table 2 (continued) Inclusion reason(s), pub year, pub type, language, study design

2018, article journal, English, quantitative

(continued)

• The present study demonstrated that the Big Five personality 2016, article traits do not account for individual differences in the degree of journal, English, lateral bias for emotion perception quantitative • This does not, however, rule out the possibility that personality traits may predict differences in the left cheek bias for emotional expression

• Additionally, it was discovered that following training to increase emotional intelligence skills, there was no statistically significant difference between the mean interpersonal connection style ratings of the students in either group (p = 0.419) • The results of this study revealed that the training provided using structured emotional intelligence skills improvement material was effective

• Students’ GPAs were significantly and adversely linked with 2018, article their total scores on self-regulated learning (p < 0.05). The journal, English, total metacognition scores did not significantly connect with quantitative student GPAs. Metacognition and self-regulation learning total scores showed statistically significant associations (p < 0.01). The overall model produced showed that the combined total scores for metacognition and self-regulation learning did not predict students’ GPAs [F (2–275) = 1.914, p > 0.005]. The present study found a significant correlation in a negative direction between self-regulated learning and students’ GPA • Regarding self-regulated learning, the present study found a significant correlation in a negative direction between self-regulated learning and student GPAs. This indicates that as one’s self-regulated learning skills increase and are used more often, GPA is diminished

Outcome/conclusion

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The Relationship between Teacher • 80 teacher Candidates’ Emotional candidates Intelligence Level, Leadership Styles and Their Academic Success (2016) Füsun Yildizbas

Emotion Regulation Ability: Test Performance and Observer Reports in Predicting Relationship, Achievement and Well-Being Outcomes in Adolescents (2021) Zorana Ivcevic and Catherine Eggers

18

19

• 220 students

• Trait Emotional Intelligence Questionnaire (TEIQue) • Big Five Inventory (BFI)

A Study of the Emotional • 240 students Intelligence and Personality Traits of University Finance Students (2021) Ana M. Rosales-Pérez, Manuel A. Fernández-Gámez, Macarena Torroba-Díaz and Jesús Molina-Gómez

17

• Emotion Regulation Ability (ERA) • Big five inventory

• Relational survey model • Emotional Intelligence Scale (EIS) • Teacher Leadership Style Scale (TLSC)

Study design

No. Journal name, authors, publication Number of year participants, participants

Table 2 (continued)

2021, article journal, English, quantitative

Inclusion reason(s), pub year, pub type, language, study design

(continued)

• The present results point to the need to understand emotion 2021, article regulation in terms of both one’s ability, the potential to journal, English, regulate emotions successfully, and observed behavior become quantitative indicators of successful emotion regulation in which when trying to predict academic and interpersonal outcomes in adolescents • Academic honors are a little less frequently employed in research, but they are conceptually significant since they signify a high degree of success and aspiration as a measure taking into account grades, but also judgments of academic motivation and academic citizenship or duty

• The multiple linear regression analysis revealed that only the 2016, article optimism sub-dimension of emotional intelligence (R = journal, English, 2 quantitative 0.316, R = 0.10, p 0.01) has a statistically low significant effect on leadership styles. It identifies 10% of the overall variation in leadership styles that are optimistic • The emotional intelligence levels and teacher leadership styles of teacher qualities are among the elements that affect education directly or indirectly • There are different results in terms of relations between emotional intelligence and academic success

• The results of the present study confirmed that there are significant differences in EI and PT levels between students and professionals in the financial industry and that such differences are associated with biases in financial behavior (p < 0.05) • Likewise, the results obtained confirmed that university students present a gap compared to professionals only in certain emotional competencies and that these are related to optimism bias, risk tolerance, self-control bias, loss aversion, and regret aversion

Outcome/conclusion

318 N. A. Saufi et al.

Emotional Intelligence and • 76 adolescents Callous–Unemotional Traits in Incarcerated Adolescents (2016) Rachel E. Kahn, Elsa Ermer, Peter Salovey and Kent A. Kiehl

21

• Wechsler Intelligence Scale for Children-Fourth Edition • The Psychopathic Checklist—Youth Version (PCL-YV) • The Inventory of Callous–Unemotional Traits • Antisocial Process Screening Device (APSD) • Antisocial Process Screening Device (APSD) • Youth Psychopathic Traits Inventory (YPI) • Measuring Emotional Intelligence in Early Adolescence (MSCEIT-YV)

• The aggression questionnaire • Test de Inteligencia • Emocional de la Fundacion Botın para Adolescentes

Ability Emotional Intelligence and Its Relation tso Aggression Across Time And Age Groups (2016) Esperanza Garcia-Sancho, Jose M. Salguero and Pablo Fernandez-Berrocal

20

• 474 undergraduate students

Study design

No. Journal name, authors, publication Number of year participants, participants

Table 2 (continued)

2016, article journal, English, quantitative

Inclusion reason(s), pub year, pub type, language, study design

(continued)

• This realm considers an individual’s ability to designate 2016, article appropriate emotions to specific scenarios as well as assign the journal, English, effectiveness of particular actions to manage or deal with quantitative situations where emotions play a role in shaping their own or others’ behaviors • Findings from the current study extend research in adult incarcerated populations and suggest that deficits in strategic EI may be present in adolescence among youth with high levels of CU traits

• Based on EI self-report measures showing a negative relationship between TEI and aggressive behavior in different age groups • Better understanding of emotional abilities in aggression may help in designing more effective prevention and intervention programs that promote the ability to inhibit such behavior

Outcome/conclusion

Understanding Emotional Intelligence and Personality to Athletes’ … 319

Intrapersonal Emotional Intelligence during Adolescence: Sex Differences, Connection with other Variables, and Predictors (2020) Maite Garaigordobil

23

• 2283 participants

• Trait Meta-Mood Scale (TMMS) • Questionnaire Measure Emotional Empathy (QQMEE) • Rosenberg Self-Esteem Scale (RSE) • Five-Factor Reduced NEO Personality Inventory (NEO-FFI) • CONFLICTALK. Questionnaire to measure the message styles in conflict management • CYBERBULLYING. Peer bullying screening. Screening of face-to-face school bullying and technological bullying (cyberbullying) • Antisocial-Delinquent Behavior Questionnaire (AD) • Scale of Parental Socialization in Adolescence (ESPA29)

• Self-report survey design • Genos Emotional Intelligence Inventory (Genos EI) • Ten-Item Personality Inventory (TIPI)

Emotional Intelligence and Personality Traits as Predictors of Occupational Therapy students’ Practice Education Performance: A Cross-Sectional Study (2016) Ted Brown, Brett Williams, and Jamie Etherington

22

• 114 s and third-year undergraduate

Study design

No. Journal name, authors, publication Number of year participants, participants

Table 2 (continued)

2017, article journal, English, quantitative

Inclusion reason(s), pub year, pub type, language, study design

• The results of the MANOVA for all the variables yielded 2021, article differences depending on the educational cycle (age-related), journal, English, Wilks’ Lambda, ⌃ = 0.994, F(3, 2077) = 3.95, p < 0.01, quantitative although the effect size was very small (ηp2 = 0.006, r = 0.07) • Adolescents with low IEI (compared to those with an average or high level) showed significantly lower empathy, self-esteem, extroversion, openness, agreeableness, responsibility, use of cooperative and passive conflict-resolution strategies as well as having parents with a low level of acceptance, a affection, and involvement in the lives of their children • School is a space where children and adolescents are in contact with their peer group and with situations that generate a diversity of emotions. For this reason, it is considered of great importance to address EI in early education • To conclude that there is a need to promote IEI and interpersonal EI as a factor in the development and the prevention of bullying/cyberbullying

• The findings showed a number of statistically significant relationships between the Genos EI variables and the TIPI subscale at the p < 0.05 and p < 0.01 level • The key findings demonstrated that measures of EI were positively related to occupational students’ fieldwork performance, specifically in the areas of professional behavior and communication skills • The results suggest that the measurement of EI may be a useful tool for some aspects of performance and a basis for improving curricula to promote self-awareness of non-cognitive attributes among occupational therapy students

Outcome/conclusion

320 N. A. Saufi et al.

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a relationship between emotional intelligence and dancers’ personality traits, especially responsibility and agreeableness. Three personality traits such as extraversion, agreeableness, and openness to experience found to be important predictors of emotional intelligence by Alghamdi, who looked into five personality traits as drivers of emotional intelligence. The way that people behave over time is influenced by their personality qualities. One’s health and lifespan are affected throughout time and cumulatively by personality qualities. It looks into how a person’s personality impacts their thoughts, feelings, and behavior. It had been proved by Ubago-Jiménez et al. (2019) stated that the present results point to the need to understand emotion regulation in terms of both one’s ability, the potential to regulate emotions successfully, and observed behavior become indicators of successful emotion regulation in which when trying to predict academic and interpersonal outcomes in adolescents. Personality traits can be used to predict outcomes for individuals, relationships, groups, and societies. A realistic view of personality processes explains individual variances. The findings of this study showed how crucial emotional intelligence and personality are for students interested in sports sciences, in contrast to the findings of Balyan et al. (2021). The most significant discovery is that emotional intelligence barely influences personal traits. Emotional intelligence and personality have been demonstrated to be incompatible. The Big Five personality traits do not account for individual differences in the magnitude of lateral bias for emotion perception, according to Fabio (2018). The potential that personality factors affect the emotional expression bias on the left cheek is not ruled out by this. This is due in part to the fact that modern personality tests do not always look at the same traits, despite being called conscientiousness, neuroticism, agreeableness, openness, and extraversion (Las Heras-Fernandez et al. 2020). In addition, it has been argued that EI and personality are closely related (Kahn et al. 2016) and that EI ought to be regarded as a personality trait (Othman et al. 2016). The results suggest that emotional intelligence and personality may be investigated more thoroughly in the next research in other disciplines.

5 Conclusion Thus concluding, this topic investigates an individual’s ability to assign appropriate emotions to certain situations and to assess the effectiveness of various activities to manage or deal with situations in which emotions impact one’s own or others’ behavior (Goleman 1995). Based on (Culha and Acaroglu 2019) findings, the authors may emphasize the importance of developing emotional intelligence at a young age for the efficacy and development of professional goals. Their goals may lead to the current path that they will choose in the future as people will tend to choose their own way after taking a new step and new life after graduating from university or high school. Understanding, controlling, and using emotional information to deal with

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daily challenges may come more naturally to people with greater EI. They consequently tend to be healthier and better acclimated to their environment. Emotions may have a greater direct impact on mental health than on physical health, which may be more influenced by healthy lifestyle choices (Ivcevic and Eggers 2021). Furthermore, according to Goleman (1995), the ability of a person to successfully regulate emotions toward goals of personal learning and development can be used to predict outcomes like personal growth, a feeling of purpose in life, and a sense of mastery in coping with life’s problems. Sports success and pleasure are also correlated with emotional intelligence (Yusoff et al. 2011). According to research findings, emotional intelligence has a potentially beneficial impact on athletes’ successes and the excellence of coaching activities. Self-control abilities and athletes’ drive to play sports and perform well are both correlated with emotional intelligence (Charbonneau and Nicol 2002). It may direct to the personality of the young athletes and will influence their characters which might impact their whole life. It is simple to realize how crucial it is for professional athletes to develop their emotional intelligence in order to increase their performance (Fabio 2018). But they also contend that earlier work on emotional intelligence is necessary for the realm of sports education. Meanwhile, the most crucial discovery, according to Balyan et al. (2021), shows that emotional intelligence does not affect personality and might vary and extend to other research for future discussions and will help to identify more the variables and factors that influence emotional intelligence and personality of young athletes. However, several issues restrict the generalizability of these studies. For researchers whose primary focus is on emotional intelligence, understanding how this construct relates to the highest-order factor in personality establishes a link between it and mainstream differential psychology models, in this case, the Big Five because more databases are available, employing only two sites (Scopus and Web of Science) may be insufficient. The findings also assist student-athletes in learning more and gaining an understanding of their behavior as it relates to their emotional intelligence and personality traits.

References Almeida F (2019) Adoption of a serious game in the development of emotional intelligence skills. Eur J Investig Health Psychol Educ 10(1):30–43. https://doi.org/10.3390/ejihpe10010004 Balyan M, Köksal A, Gönkek P, Zekio˘glu A, Ba¸so˘glu UD (2021) Analysıs of emotional intelligence and personality traits of students in faculty of sports sciences. Propósitos y Representaciones 9(SPE3). https://doi.org/10.20511/pyr2021.v9nspe3.1157 Charbonneau D, Nicol AAM (2002) Emotional intelligence and prosocial behaviors in adolescents. Psychol Rep 90(2):361–370. https://doi.org/10.2466/pr0.2002.90.2.361 Culha Y, Acaroglu R (2019) The relationship amongst student nurses’ values, emotional intelligence, and individualised care perceptions. Nurs Ethics 26(7–8):2373–2383. https://doi.org/10.1177/ 0969733018796682 De Las Heras-Fernandez R, Espada M, García-Coll V, Anguita JM (2020) Emotional intelligence of Spanish dancers and its relationship with personality traits. J Phys Educ Sport 20(5):2586–2594. https://doi.org/10.7752/jpes.2020.05353

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Di Fabio A, Saklofske DH (2018) Personality and individual differences the contributions of personality and emotional intelligence to resiliency. Pers Individ Diff 123(November 2017):140–144. https://doi.org/10.1016/j.paid.2017.11.012 Galea S, Lindell AK (2016) Do the Big Five personality traits predict individual differences in the left cheek bias for emotion perception? Laterality 21(3):200–214. https://doi.org/10.1080/135 7650X.2016.1146738 Goleman D (1995) Emotional intelligence. Kairós, New York, NY, USA Ivcevic Z, Eggers C (2021) Emotion regulation ability: test performance and observer reports in predicting relationship, achievement and well-being outcomes in adolescents. Int J Environ Res Public Health 18(6):3204. https://doi.org/10.3390/ijerph18063204 Kahn RE, Ermer E, Salovey P, Kiehl KA (2016) Emotional intelligence and callous—unemotional traits in incarcerated adolescents. Child Psychiatry Hum Dev. https://doi.org/10.1007/s10578015-0621-4 Mayer JD, Caruso DR, Salovey P (2016) The ability model of emotional intelligence: principles and updates. https://doi.org/10.1177/1754073916639667 Othman CN, Yusof MSB, Din AM, Zakaria LA (2016) Emotional intelligence and personality traits in relation to psychological health among pharmacy students in Malaysia. Procedia Soc Behav Sci 222:253–262. https://doi.org/10.1016/j.sbspro.2016.05.154 Petrides KV, Siegling AB, Saklofske DH (2016) Theory and measurement of trait emotional intelligence Piepiora P (2021) Personality profile of individual sports champions. In: Brain and behaviour, vol11, Issue 6. https://doi.org/10.1002/brb3.2145 Ubago-Jiménez JL, González-Valero G, Puertas-Molero P, García-Martínez I (2019) Development of emotional intelligence through physical activity and sport practice. A systematic review. Behav Sci 9(4):44. https://doi.org/10.3390/bs9040044 Van Der Linden D, Tsaousis I, Petrides KV (2012) Overlap between general factors of personality in the big five, giant three, and trait emotional intelligence. Pers Individ Diff 53(3):175–179. https://doi.org/10.1016/j.paid.2012.03.001 Yusoff MS, Rahim AF, Mat Pa MN, See CM, Ja’afar R, Esa AR (2011) The validity and reliability of the USM Emotional Quotient Inventory (USMEQ-i): its use to measure emotional quotient (EQ) of future medical students. Int Med J 18(4):293–299

Association of Arch Height of the Foot and Jump Capacity in Youth Soccer Athletes Shariman Ismadi Ismail , Fatin Sabrina Nor Azian, Rahmat Adnan , Siti Zulaikha Kamil, Amir Adri Nun Arimanshah, Norasrudin Sulaiman, Motohide Arayama, Raja Mohammed Firhad Raja Azidin, Johan Kamal Hamidon, Mohamad Mohd Sadek Mustafa, and Mohad Anizu Mohd Nor Abstract This study was aimed to find whether there is an association between foot arch height index (AHI) and jump capacity (vertical jump test = VJT and horizontal jump test = HJT) in youth soccer athletes. A total of 45 youth male soccer athletes were recruited in this study (age = 20.2 ± 1.1 and BMI = 21.7 ± 1.8). Both feet of all the players were scanned using a three-dimensional scanning system, and the players AHI were calculated and clustered into three subgroups (Group 1–3: G1, G2 and G3). The association between AHI subgroups and jumping capacity was analyzed using analysis of covariates (ANCOVA) statistical test. A significant positive association (p < 0.05) between AHI G1 and G2 subgroups with horizontal jump capacity (HJT) was identified. However, no association between all AHI subgroups with vertical jump capacity (VJT) was found. It was suggested that youth soccer athletes with lower foot arch height (G1 and G2) may benefited from their lower foot length and foot instep height ratio during horizontal jump test as compared to G3 subgroups. This study has successfully demonstrated and identified AHI as an important parameter that is associated with soccer player jumping performance, specifically for horizontal jump as found in this study. Keywords Foot arch · Arch height index (AHI) · Leg power · Horizontal jump · Vertical jump · Soccer · Football · Youth

S. I. Ismail · F. S. N. Azian · R. Adnan (B) · S. Z. Kamil · A. A. N. Arimanshah · N. Sulaiman · R. M. F. R. Azidin · M. M. S. Mustafa · M. A. M. Nor Faculty of Sport Science and Recreation, Universiti Teknologi MARA, Shah Alam, Malaysia e-mail: [email protected] M. Arayama Dream GP Inc., Osaka, Japan J. K. Hamidon Selangor Football Club (FC), Shah Alam, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_26

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1 Introduction Soccer is a sport that is characterized by multidirectional dynamic limbs movement such as sprinting, quick acceleration, deceleration, and change of direction (Kaplan et al. 2009; Martínez-Hernández et al. 2022) as well as explosive movement such as jumping. Jumping tasks are typically characterized by large forces application on to the musculoskeletal systems. Moreover, jumping is a crucial movement in soccer, and it was reported soccer players at most to perform jumping as much as 36 times during a soccer match (Mohr et al. 2003). Such high frequency and high loading of jumping would require a mechanical support system that stabilize human body during executing jumping movement (Fuerst et al. 2021). The aspect of lower limbs is often discussed as one of the main focused area in recent football research (Arundale et al. 2020; Bastiaansen et al. 2022; Frias Bocanegra and Fong 2022; Roughead et al. 2022). Among the main focused area, the prevalence of foot arch was discussed from the perspective of injury mechanism and prevention, as well as performance (Han et al. 2015; Huang et al. 2022). Foot arch is one of the most important aspects in lower limb functional ability that may influence performance in sports (Knapik et al. 2014). Foot arch can be classified based on the arch height index (AHI) (Williams and McClay 2000). Past studies have shown that AHI have direct influence in the running performance (Knapik et al. 2014; Wo´zniacka et al. 2013). In addition, it was reported that foot structure has potentially influenced jumping performance untrained school children (Raja Sekhar and Kumar 2012). This could be possible due to athletes with lower AHI have shown to possessed relatively higher ankle muscle strength as compared to the ones with higher AHI (Zhao et al. 2017). In contrast, there were also reports that have shown that foot arch may not be effective enough in accounting for jumping performance among young adults (Lizis et al. 2010) and children (Morita et al. 2015). Therefore, it remains unclear on whether the foot arch can be associated with jumping performance, specifically among younger soccer athletes. This warrants further clarification. In this study, we aim to explore whether there are differences in jump capacity among participants with different AHI and association between the foot arch height index (AHI) and jumping capacity in youth soccer athletes. It has been hypothesized that there are significant differences between participants with different AHI subgroups. It is also hypothesized that there will be associations between the AHI value and vertical and horizontal jump performance (leg power capacity) in youth soccer athletes, specifically for participants with lower AHI.

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2 Methodology 2.1 Participants This study involved forty-five male young elite athletes (n = 45, age = 20.2 ± 1.1, BMI = 21.7 ± 1.8) that are registered with a professional soccer club. The inclusion criteria were male, under-21 (U21) from age of 19 to 21 years old and had no lower limb injury history in the past 6 months. The study was approved by University Research Ethics Committee, and all participants have read and signed an inform consent document prior to the starts of the study.

2.2 Arch Height Index (AHI) A three-dimensional (3D) Footstep PRO Scanner (Dream GP Inc., Osaka, Japan) was used to capture foot structure of all participants. The foot arch height index (AHI) was calculated in accordance to the procedure used in the past studies (Saghazadeh et al. 2015a, b). Participants were instructed to stand with bare feet with one foot is placed onto the center of the scanner with proper positioning and the opposite foot is placed on a platform outside the scanner (Fig. 1). Instructions were given to the participants to remain still and look straight ahead during the scanning time (Saghazadeh et al. 2015b). The same procedure is repeated for another foot, and the measurement was collected twice on each person for right and left feet in standing position. Data from the foot scanning process will be captured and stored in laptop which runs the 3D scanning software system (Dream GP Inc., Osaka, Japan). The AHI subgroups calculated based on total foot length and insteps height data obtained from the scanning, using the standard formula defined from past study (McPoil et al. 2008): AHI = height of insteps/total foot length.

2.3 Jump Capacity Participants were instructed to performed horizontal and vertical jump to measure jump capacity. A commercial plastic swivel vane attached on the top part of a metal pole participants’ reach height is adjusted to the lowest van for vertical jump test (VJT). From an erect position, player then lower down the body and bend the knees slightly at the same time swinging both arms to achieve maximal upward drive while using dominant hand to displace the highest possible vane. Player land on both of the feet at the same time, and jump height was determined based on the number of vanes displaced in centimeter (cm). Each of the participants was required to perform the jump three times, and the best measurement out of the three trials is selected for analysis.

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Fig. 1 Three-dimensional footstep PRO scanner (Dream GP Company, Osaka, Japan) was used to measure the foot insteps height and total foot length

For horizontal jump test (HJT), 50 m measuring tape (Skylon, USA) is used in this study to measure the length of horizontal jump performed by the participants. From a standing position, participant performed horizontal jump by swinging the arms and bending the knees to provide full forward drive. The jump-length measurement from the take-off line (0 m position of the measuring tape) to the nearest landing contact point from the back of the heels of the participants is measured by referring to the measuring tape scale.

2.4 Statistical Analysis Statistical analyzes were performed using IBM SPSS Statistics 22 (SPP Inc., Chicago, IL, USA). The normality and homogeneity of variances within the data were confirmed with the Shapiro–Wilk and Levene’s tests, respectively. In addition, participants are divided into three cluster subgroups. The clustering of three subgroups was divided according to past study by Saghazadeh et al. (2014). First subgroup cluster, AHI G1 is based on the AHI of the mean < 0.23. The second subgroup cluster, AHI G2 is based on the AHI mean 0.23–0.25. The third subgroup cluster, AHI G3 is based on the AHI mean > 0.25. The variables that are normally distributed were analyzed using one-way ANOVA test (ANOVA) to examine for any possible group differences. However, if the variables are not normally distributed, Kruskal–Wallis H test were used to examine for any possible group differences. Furthermore, the associations between AHI subgroups and jump capacity (VJT and HJT) was determined using analysis of covariates (ANCOVA) with potential confounders: age, height, and weight were controlled. The statistical significance was set at p < 0.05.

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Prior to the association’s analysis between AHI and jump capacity was computed, difference between the right foot AHI and left foot AHI for all participants was determined. Study found no difference between left and right foot AHI from WilcoxonSigned Ranks test. Hence, the mean of AHI for both feet were computed for inferential analysis.

3 Results 3.1 BMI, Foot Instep Height, and Total Foot Length Forty-five individuals participated in this study and clustered into three subgroups of foot arch, namely AHI G1(n = 13), AHI G2(n = 15), and AHI G3(n = 17). It was found that there was no significant difference between AHI subgroups (p < 0.05) BMI (Table 1). Furthermore, as shown in Table 1, AHI G3 subgroup showed a significantly higher height of foot instep (65.8 ± 2.0 mm) compared to AHI G1 and G2 subgroups (p < 0.05). In addition, AHI G2 subgroup (62.0 ± 2.0 mm) also showed a significantly high height of foot instep compared to AHI G1 subgroup (60.1 ± 2.6 mm). AHI G1 subgroup also has showed a significantly (p < 0.05) longer total foot length (268.7 ± 9.1 mm) compared to AHI G2 (258.2 ± 7.7 mm), and AHI G3 subgroups (260.2 ± 10.2 mm).

3.2 Jump Capacity As shown in Table 1, no significant difference was observed between AHI subgroups (p > 0.05) in jumping performance for both VJT [G1: (53.7 ± 6.8 cm); G2: (50.4 ± 6.3 cm); G3: (53.6 ± 7.9 cm)] and HJT [G1: (2.3 ± 0.2 m); G2: (2.2 ± 0.2 m); G3: (2.3 ± 0.3 cm)].

3.3 Association Between AHI and Jump Capacity There is a significant association between AHI subgroups and HJT after height has been controlled (p = 0.07) as shown in Table 2. Specifically, a positive association between AHI G1 (β = 0.02, p = 0.013) and AHI G2 (β = 0.02, p = 0.04) subgroups and HJT has been observed. However, no association (p > 0.05) between all AHI subgroups and VJT was identified.

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Table 1 Body Mass Index (BMI), height of foot instep, total foot length, and jump capacity based on AHI subgroups BMI

Height of foot instep (mm)

Total foot length (mm)

Vertical jump (cm)

Horizontal jump (m)

AHI subgroups

Mean

G1 (n = 13)

22.1

G2 (n = 15) G3 (n = 17)

SD

95% CI

Sig

2.3

21.0–23.2

0.450A

21.3

1.7

20.5–22.1

21.9

1.8

20.0–23.8

G1 (n = 13)

60.1LM

2.6

58.8–61.3

G2 (n = 15)

62.0LN

2.0

61.1–63.0

G3 (n = 17)

65.8MN

2.0

63.7–67.9

G1 (n = 13)

268.7L

9.1

264.5–273.0

G2 (n = 15)

258.2L

7.7

254.5–261.9

G3 (n = 17)

260.2

10.2

249.4–270.9

G1 (n = 13)

53.7

6.8

50.5–56.9

G2 (n = 15)

50.4

6.3

47.4–53.5

G3 (n = 17)

53.6

7.9

45.3–61.9

G1 (n = 13)

2.3

0.2

2.2–2.3

G2 (n = 15)

2.2

0.2

2.1–2.3

G3 (n = 17)

2.3

0.3

2.0–2.3

0.000A

0.002A

0.299A

0.654K

SDstandard deviation, CI confident interval, Sig significant, K Kruskal Wallis, A One way ANOVA; AHI G1 versus AHI G2: 1, AHI G1 versus AHI G3: 2, AHI G2 versus AHI G3: 3. The significance level was set at p < 0.05*

4 Discussion This study examined whether there is a significant difference in jump capacity between AHI subgroups and an association between foot arch index (AHI) and leg power capacity (VJT and HJT) among youth soccer athletes. It was hypothesized that there are significant differences between the AHI subgroups in VJT and HJT performance. We also have hypothesized that there is a significant G1 and G2 foot arch (relatively lower AHI compared to G3) is associated with leg power capacity in youth soccer athletes. In contrast to our hypothesis, no significant differences between all the AHI subgroups on both VJT and HJT were identified. The study confirmed low and normal foot arch in G1 and G2 have significant influence on leg power, as represented by the jumping performance during forward jumping (HJT) among soccer athletes. However, foot arch has no association on leg power in vertical jumping. This study has confirmed that AHI may not be efficient as a jumping performance indicator. This is in line with several past studies which have reported that foot arch may not influence jumping performance (Lizis et al. 2010; Morita et al. 2015). However, this study has also revealed interesting insight that different foot arch is associated to the horizontal jumping performance among youth soccer athletes. It is possible that, in the past studies where foot arch was found not to significantly

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Table 2 ANCOVA statistical test on the association between AHI subgroups and jump capacity Horizontal Jump Test (HJT) Intercept AHI G1

Mean

SD

β

Sig

2.144

0.001

90% CI

Sig. groups 0.007*

2.3

0.2

0.002

0.013*

0.000–0.003

Age

19.1

1.0

−0.076

0.221

−0.201 to 0.050

Height

78.9

87.6

0.001

0.513

−0.002 to 0.015

Weight

66.6

6.2

−0.003

0.706

−0.021 to 0.015

AHI G2

2.2

0.2

0.002

0.004*

0.001 to 0.003

Age

19.0

0.9

0.008

0.891

−0.113 to 0.129

Height*

63.1

82.6

0.002

0.010

0.001–0.003

Weight

61.1

5.5

−0.001

0.978

−0.017 to 0.018

AHI G3

2.3

0.3

0.001

0.100

0.000–0.002

18.3

0.8

0.090

0.740

−0.931 to 0.112

Height

115.1

88.0

0.004

0.243

0.006–0.086

Weight

63.2

6.1

−0.031

0.372

−0.148 to 0.086

β

Sig

90% CI

Age

Vertical Jump Test (VJT) Intercept

Mean

AHI G1

53.7

Age Height

SD

−2.099

0.960

6.8

32.745

0.191

19.1

1.0

−1.839

0.347

−5.863 to 2.185

78.9

87.6

−0.041

0.110

−0.092 to 0.010

Weight

66.6

6.2

0.256

0.357

−0.316 to 0.827

AHI G2

50.4

6.3

31.009

0.216

−9.502 to 3.230

Age

19.0

0.9

0.862

0.657

−3.195 to 4.919

Height

63.1

82.6

0.039

0.096

−0.008 to 0.086

Weight

61.1

5.5

0.402

0.165

−0.185 to 0.988

AHI G3

52.3

7.9

32.090

0.190

−6.236 to 6.419

Age

18.3

0.8

2.724

0.792

−36.215 to 41.663

Height

115.1

88.0

0.043

0.682

−0.346 to 0.431

Weight

63.2

6.1

−1.170

0.377

−5.634 to 3.295

Sig. groups 0.087

AHI arch height index, SD standard deviation, Sig significant, CI confident interval The significance level was set at p < 0.05*

contributed on jump performance, the participants which have involved in those studies may have not involved similar training experience among them. This particular aspect could have potentially masked the foot arch influence on their jump performance, as reported in those studies. Associations found in AHI G1 and G2 in horizontal jump performance may have suggested that these subgroups may benefitted by their relatively lower AHI during horizontal jump execution. This finding

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has also partially explained where in the past study (Zhao et al. 2017), it was found that participants that possessed lower AHI would also produce relatively higher ankle muscle strength as compare to the participants that possessed higher AHI. These characteristics were not found in AHI G3 subgroup. It is possible that AHI G3 subgroup do not depends on their ankle muscle and could have utilized different mechanism as compared to AHI G1 and G2 during horizontal jump execution. Our study is the first research that has reported findings which suggested the foot with lower AHI (G1 and G2) could potentially influenced horizontal jump execution among youth soccer athletes. On a different note, no association between vertical jump performance and AHI was observed in this study. Differences in the mechanism of execution during vertical and horizontal jump may account for the different role of AHI results found in this study during VJT and HJT. There is a need for further clarification of these findings as there could be other factors that could have influenced findings reported in this study. Nonetheless, further understanding on the aspect of jump mechanism could be utilized to help improve jump performance in soccer or any other sports with similar attributes.

5 Conclusion This study has confirmed youth soccer athletes with different foot AHI have similar jumping performance. However, it was identified that participant with lower AHI (G1 and G2) may have benefitted their lower foot arch characteristics and have utilized this function in horizontal jump execution. Therefore, by identifying suitable players foot characteristics in AHI may help further understand jump mechanism in soccer athletes. Advanced knowledge on jump mechanism could potentially help to improve jump performance. Acknowledgements The authors would like to thank Selangor Football Club and Dream GP Inc. for the cooperation in this study.

References Arundale AJH, Kvist J, Hägglund M, Fältström A (2020) Jump performance in male and female football players. Knee Surg Sports Traumatol Arthrosc 28(2):606–613. https://doi.org/10.1007/ s00167-019-05747-1 Bastiaansen BJ, Vegter RJ, Wilmes E, de Ruiter CJ, Lemmink KA, Brink MS (2022) Biomechanical load quantification using a lower extremity inertial sensor setup during football specific activities. Sports Biomech, pp 1–16. https://doi.org/10.1080/14763141.2022.2051596 Frias Bocanegra JM, Fong DTP (2022) Playing surface traction influences movement strategies during a sidestep cutting task in futsal: implications for ankle performance and sprain injury risk. Sports Biomech 21(4):380–390. https://doi.org/10.1080/14763141.2021.1980606

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Fuerst P, Gollhofer A, Wenning M, Gehring D (2021) People with chronic ankle instability benefit from brace application in highly dynamic change of direction movements. J Foot Ankle Res 14(1):13. https://doi.org/10.1186/s13047-021-00452-0 Han J, Anson J, Waddington G, Adams R, Liu Y (2015) The Role of ankle proprioception for balance control in relation to sports performance and injury. Biomed Res Int 2015:842804. https://doi. org/10.1155/2015/842804 Huang S, Zhang HJ, Wang X, Lee WC, Lam W-K (2022) Acute effects of soleus stretching on ankle flexibility, dynamic balance and speed performances in soccer players. Biology 11(3). https:// doi.org/10.3390/biology11030374 Kaplan T, Erkmen N, Taskin H (2009) The evaluation of the running speed and agility performance in professional and amateur soccer players. J Strength Conditioning Res 23(3):774–778 Knapik JJ, Trone DW, Tchandja J, Jones BH (2014) Injury-reduction effectiveness of prescribing running shoes on the basis of foot arch height: summary of military investigations. J Orthop Sports Phys Ther 44(10):805–812 Lizis P, Posadzki P, Smith T (2010) Relationship between explosive muscle strength and medial longitudinal arch of the foot. Foot Ankle Int 31(9):815–822. https://doi.org/10.3113/FAI.2010. 0815 Martínez-Hernández D, Quinn M, Jones P (2022) Linear advancing actions followed by deceleration and turn are the most common movements preceding goals in male professional soccer. Sci Med Football, pp 1–9. https://doi.org/10.1080/24733938.2022.2030064 McPoil TG, Martin RL, Cornwall MW, Wukich DK, Irrgang JJ, Godges JJ (2008) Heel pain—plantar fasciitis. J Orthop Sports Phys Ther 38(4):A1–A18 Mohr M, Krustrup P, Bangsbo J (2003) Match performance of high-standard soccer players with special reference to development of fatigue. J Sports Sci 21(7):519–528. https://doi.org/10.1080/ 0264041031000071182 Morita N, Yamauchi J, Kurihara T, Fukuoka R, Otsuka M, Okuda T, Ishizawa N, Nakajima T, Nakamichi R, Matsuno S, Kamiie S (2015) Toe flexor strength and foot arch height in children. Med Sci Sports Exer 47(2):350–356. https://doi.org/10.1249/MSS.0000000000000402 Raja Sekhar KV, Kumar R (2012) Medial side foot length from the horizontal axis of the ankle and Foot area while standing plantar flexed as determinants in long jump performance among previously untrained school children. Int Online Phys Educ Sports Res J 1(3):1–5 Roughead EA, King MG, Crossley KM, Heerey JJ, Lawrenson PR, Scholes MJ, Semciw AI, Mentiplay BF, Kemp JL (2022) Football players with long standing hip and groin pain display deficits in functional task performance. Phys Ther Sport 55:46–54. https://doi.org/10.1016/j. ptsp.2022.02.023 Saghazadeh M, Tsunoda K, Okura T (2014) Foot arch height and rigidity index associated with balance and postural sway in elderly women using a 3D foot scanner. Foot Ankle Online J 7(1):10–3827 Saghazadeh M, Kitano N, Okura T (2015a) Gender differences of foot characteristics in older Japanese adults using a 3D foot scanner. J Foot Ankle Res 8(1):1–7 Saghazadeh M, Tsunoda K, Soma Y, Okura T (2015b) Static foot posture and mobility associated with postural sway in elderly women using a three-dimensional foot scanner. J Am Podiatr Med Assoc 105(5):412–417 Williams DS, McClay IS (2000) Measurements used to characterize the foot and the medial longitudinal arch: reliability and validity. Phys Ther 80(9):864–871. https://www.ncbi.nlm.nih.gov/ pubmed/10960934 Wo´zniacka R, Bac A, Matusik S, Szczygieł E, Ciszek E (2013) Body weight and the medial longitudinal foot arch: high-arched foot, a hidden problem? Eur J Pediatr 172(5):683–691 Zhao X, Tsujimoto T, Kim B, Tanaka K (2017) Association of arch height with ankle muscle strength and physical performance in adult men. Biol Sport 34(2):119–126

The Relationship Between Leg Preference and Bilateral Asymmetry in Muscular Strength Among Taekwondo Athletes Sarina Md Yusof and Muhd Ithar Haziq

Abstract Every athlete tends to have a bias on a leg in performing a specific task during sports performance. This event will eventually cause bilateral deficit or bilateral asymmetry in muscular strength. Differently for a non-laterally dominant sport like Taekwondo, the athletes were required to have equal strength and control on both their dominant and non-dominant legs. It is also inexact to settle the preferred leg as the dominant leg as it varies in different athletes influenced by individual preference, sports requirements, and nature. The purpose of this study was to determine the relationship between leg preference and bilateral asymmetry in muscular strength among Taekwondo athletes. This study also aims to study the agreement between self-reported and observed leg preferences. The final objective of this study is to determine the difference in muscular strength between the dominant and nondominant legs. A total of 17 Taekwondo athletes with at least an experience in national level Taekwondo championships were recruited for this study. All athletes underwent two (2) methods of leg preference resolution (self-reported and observed) and isokinetic testing. No significant relationship was found between leg preference and muscular strength asymmetry. There was also an agreement between self-reported and observed leg preference determination methods. Finally, we also learned that there was no significant difference in muscular strength between dominant and nondominant legs among Taekwondo athletes. In conclusion, this study validated that Taekwondo athletes have a balanced overall ratio of interlimb muscular strength and within normal range below 10%. Keywords Bilateral asymmetry · Muscular strength · Taekwondo

S. M. Yusof (B) · M. I. Haziq Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_27

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1 Introduction 1.1 Background of Study Taekwondo is an Olympic sport that boasts a vast audience in various countries around the globe. Unlike other combat sports, Taekwondo is unique as it predominantly utilizes the lower extremity muscles (Var 2019). The word Taekwondo was derived from Korean words which covey “Tae” kicking by the ply of the foot, “Kwon” means striking by a ply of the hand or fist, and “Do” means way or discipline (Var 2019). Taekwondo was just a demonstration sport until its first debut as an official medal sport at the 2000 Sydney Games. Taekwondo as a sport can be divided into two events that are kyorugi and poomsae. Both Taekwondo events are well-known for their kicking height and foot techniques (Atasoy et al. 2018). Studies regarding the relationship between leg preference or dominance and muscular strength may provide relevant information driving toward the enhancement of sports performance (e.g., technical skill execution, gait analysis, and conditioning) (Sliwowski et al. 2017) and clinical evaluation such as injury prevention and rehabilitation (Promsri et al. 2020). Taekwondo Championships are organized continually every month in Malaysia. Participants selected in this study are considered elites on account of their participation in national level championships (e.g.: MASUM, SUKMA, SUKIPT, Milo National and National Interclub). MASUM, SUKMA, and SUKIPT are the examples of the most competitive championship in Malaysia. As the requirement of participation is only selected athletes from states, clubs and universities were permitted to compete. Leg preference is the possible cause of asymmetry in the flexibility and strength of the lower extremities between the two legs or between the agonist and antagonist muscles (Daneshjoo et al. 2013). Unlike other laterally dominant sports (e.g.: Fencing, Badminton) (Guan et al. 2018), Taekwondo is a non-laterally dominant sport as the movements involve both sides of the body equally requiring equal mastery of the techniques with the dominant and non-dominant legs. The bilateral asymmetry may lead to reduced postural control when performing a unilateral stance using the weak side, which may increase the risk of injury (Guan et al. 2020). Previous studies have reported higher injury risk in healthy adults (Promsri et al. 2020) and collegiate and club athletes (Abd Rahman and Shaharudin 2018) when there is an interlimb asymmetry within the legs. Strength measurements are highly significant and important on account to prevent possible injuries and for physical fitness enhancement purposes among athletes. By utilizing the isokinetic dynamometers as an instrument to determine the muscle balance and strength between the dominant/non-dominant limbs, the results obtained may assist coaches to evaluate their athletes (Var 2019). Numerous researchers have successfully explored the isokinetic muscle strength profile between the leg of preference or dominance in various sports, especially soccer (Frutuoso et al. 2016; Sliwowski et al. 2017). Most of the previous studies

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done regarding muscular strength was on either self-reported or observed leg dominance. Only one study has been done to observe the agreement between self-reported leg dominance and observed leg dominance in muscular strength among soccer athletes by Van Melick et al. (2017). However, there is a limitation within majority of the studies, as there is lack of research covering Taekwondo-specific championship and the agreement between self-reported and observed leg dominances in muscular strength asymmetry. This study is essential to quantify if self-reported leg dominance rectifies to observed leg dominance.

1.2 Research Problem Numerous researchers have successfully explored the isokinetic muscle strength profile between leg of preference or dominance in various sports, especially soccer (Frutuoso et al. 2016; Sliwowski et al. 2017). Most of the previous studies done regarding muscular strength was on either self-reported or observed leg dominance. Only one study has been done to observe the agreement between self-reported leg dominance and observed leg dominance in muscular strength among soccer athletes by Van Melick et al. (2017). However, there is a limitation within majority of the studies, as there is lack of research covering Taekwondo-specific championship and the agreement between self-reported and observed leg dominances in muscular strength asymmetry. This study is essential to quantify if self-reported leg dominance rectifies to observed leg dominance. Olympic Taekwondo is famed by its very dynamic sports fighting (Górski and Orysiak 2019). Athletes that have preference over a leg might develop muscular strength asymmetry that may further impair dynamic balance ability. However, there is very little concentration in literature that has committed to examine the muscular strength of the non-kicking leg which will be in charge of the stabilization (dynamic balance) task during kicking performance.

2 Participants Seventeen Taekwondo athletes with a mean age of 21.29 (standard deviation = 2.31) years were recruited to participate in this study. Participants must be a kyorugi athlete with at least an experience in a national level Taekwondo championship. The athletes were also screened with no injury history for the past six months. All participants were assigned to an isokinetic dynamometry task to measure both of their lower legs’ muscular strength. All procedures performed in studies involving human participants were in accordance with the ethical standards of the University Research Ethics Committee. Informed consent was obtained from all participants included in the study.

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3 Methodology 3.1 Introduction The inclusion criteria featured 17 Taekwondo athletes aged from 18 to 26 years old who had participated for at least in a national level Taekwondo competition such as Sukan Institut Pengajian Tinggi (SUKiPT), Majlis Sukan Universiti Malaysia (MASUM), Sukan Malaysia (SUKMA), and Taekwondo Malaysia National Selection Championship. The participants were also has been regularly training for the past 6 months with no history of major lower limb injury or disease. All participants participated voluntarily in this study. Participants’ height and weight were measured prior to testing procedure. The participants were verbally informed about the study method used as well as the purpose and risks of the study. A written informed consent was also obtained from each participant. The testing involved both of the dominant and non-dominant sides to fulfill the study purposes. All testing procedures were conducted in Universiti Teknologi MARA Faculty of Sports Science and Recreation’s Physiology Lab and Gymnasium. An isokinetic muscle testing system (EasyTech Prima Plus, EasyTech, Italy) was used for measurement of lower limb muscular strength protocols or variables.

3.2 Research Design This study adopted the non-experimental correlational research design. This study was non-experimental as participants were not given any treatment or interventions that may affect the isokinetic muscular strength testing. The research design was selected to identify the relationship between leg preferences on muscular strength among Malaysian Taekwondo athletes. The research findings will then be generalized to Malaysian Taekwondo athlete population. Research Paradigm See Fig. 1. IV: Leg preference (Left or Right). Research Paradigm

LEG PREFERENCE Fig. 1 Intended research paradigm

MUSCULAR STRENGTH

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DV: Muscular strength.

3.3 Population/Sample/Subjects/Sampling Techniques Subjects recruited were Malaysian Taekwondo athletes who have participated in at least a national level Taekwondo championship from 2017. The athletes were recruited via purposive sampling. There was a total of 17 athletes (8 male and 9 female) participated in this study.

3.4 Instrumentation 3.4.1

Isokinetic Dynamometer (EasyTech Prima Plus, EasyTech, Italy)

Testing procedures using the EasyTech Prima Plus isokinetic dynamometer in the Universiti Teknologi MARA Faculty of Sports Science and Recreation’s Physiology Lab. A programmed control allows the dynamometer to provide a continuous motion at a constant speed (passive mode) and to simulate isotonic and hydrodynamic works.

3.5 FIFA Standard Soccer Ball Size 5 soccer ball (adult/professional) can be used for ball kick task to determine the observed leg preference among Taekwondo athletes. According to FIFA, a size 5 ball is between 27 and 28 inches in circumference.

3.6 Data Collection (Procedures) 3.6.1

Leg Preference Determination

Participants were asked about their self-reported leg preference in the consent form given minimum 3 days prior to testing day. While for the observed leg preference, participants performed the ball kick task. The leg chosen by participant to kick the ball was considered as the observed leg preference.

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S. M. Yusof and M. I. Haziq

Isokinetic Test

An isokinetic muscle testing system (EasyTech Prima Plus, EasyTech, Italy) was used to assess the hamstring and quadriceps strength of the subjects. Before each testing session, the dynamometer was gravitationally corrected in accordance to the manufacturer’s standardized recommendations. The participants performed a 15-min warm-up procedure with basic warm-up and calisthenic movements, and dynamic stretching exercises are focusing on the lower limbs to prevent any active generated injury risks and physically prepare the participants for the testing procedure. Participants were seated on the chair and adjusted to the optimal position. The participants were stabilized with straps across the shoulder, waist, and hips to limit extraneous movement that may affect the test results. The cuff of the dynamometer lever arm was attached to the proximal malleoli of the participant’s ankle. Dynamometer orientation was fixed at 90° and tilted at 0°, while the seat orientation will be fixed at 90° and the seatback tilted at 75°–85°. Participants performed an active submaximal effort of extension and flexion movements. During these movements, the average position of the knee joint axis was qualitatively monitored to be as close to the crank axis as possible. All participants were instructed to grasp on to either the chest straps or the handles next to the seat during all maximal trials. All maximal eccentric contraction trials were performed through a range of 90°–0° knee flexion and extension. This test speed was adopted as it was proven to be accepted as one of the fastest, yet safest, speed to test muscle contraction reliably. Encouragements by verbal coaching and visual feedback were given to all subjects to help them to direct their focus on the quality of their movements. The order of testing was randomized for the dominant and non-dominant legs to eliminate the order effect, and participants were given 3 min break resting interval while the machine setting is changed for the opposite leg by the researcher.

3.7 Data Analysis Statistical Package for the Social Science (IBM SPSS version 26.0) was used for data processing. All result values and anthropometrical data were expressed in mean and standard deviation (Mean ± SD). Descriptive statistics was used to describe the basic features of the study (i.e., participants’ height, weight, and age). Inferential statistics (Simple Linear Regression) was used to study if significant relationship exists between leg preference and bilateral asymmetry in muscular strength. Significance value (p) was to be fixed at the conventional 95% (0.05) (Table 1). To evaluate the magnitude of bilateral asymmetry in muscular strength between dominant leg and non-dominant legs, the bilateral asymmetry index was calculated as follows: Bilateral asymmetry index =

(Dominant Leg) − (Non - dominant Leg) × 100%. (Dominant Leg) + (Non - dominant Leg)

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Table 1 Inferential analysis of variables Null hypothesis

Variables

Statistical technique proposed

There is no significant relationship between leg preference and bilateral asymmetry in muscular strength among Taekwondo athletes

Leg preference (independent variable)

Paired T-test and Simple Linear Regression

Muscular strength asymmetry (dependent variable)

The index was adapted from a previous study done by Kobayashi et al.

3.8 Sample Size Sample size was determined and computed using G-power 3.1.9.7 statistical analysis program.

4 Results Table 2 shows the total mean and SD for subjects in this study which was (21.29 ± 2.31) with minimum age at 18 and maximum age at 26. Meanwhile, the mean and SD weight of all the subjects was (165.35 ± 6.08) kg with the heaviest subject weight at 96 kg and the lightest subject weight at 47 kg. Finally, the mean and SD height of all the subjects was (60.41 ± 14.26) with the tallest subject with a height of 176 cm and shortest subject with a height of 153 cm. The wide range of weight and height is due to athletes from different weight classes. Table 3 shows that leg preference does not significantly predict bilateral strength deficit or asymmetry, β = −0.161, t = −0.98, p = 0.341. In Table 4, there were an agreement between self-reported leg preference (1.18 ± 0.529) and observed leg preference (1.18 ± 0.395); t (16) = 0.000, p = 1.000. No significant difference was found (in Table 5) between the dominant leg (extension = 2.77 ± 0.45, flexion = 1.44 ± 0.39); t (17) = 0.477, p = 0.640 and non-dominant leg (2.74 ± 0.49, 1.42 ± 0.36); t (17) = 0.596, p = 0.559. Table 2 Subjects’ demographic data N

Min

Max

Mean (SD)

Age

17

18

26

21.29 (2.31)

Weight (kg)

17

153.0

176.0

165.35 (6.08)

Height (cm)

17

47.0

96.0

60.41 (14.26)

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Table 3 Regression analysis summary for leg preference predicting bilateral asymmetry in muscular strength Variable

B 0.08

−0.07 0.23

−0.161

−0.51 0.18

(Constant) Left-leg dominance

95% CI

β

−0.25

t

p

1.13

0.28

−0.98

0.34

Table 4 Agreement between self-reported leg preference and observed leg preference Mean (SD)

Paired differences CI

Self-reported -Observed Leg preference

1.18 (0.529) 1.18 (0.395)

Table 5 Isokinetic knee strength (Nm kg−1 ) for the dominant and non-dominant legs

Upper

Lower

−0.182

0.182

t

df

Sig. (2-tailed)

0.000

16

1.000

Dominant leg

Non-dominant leg

P-value

Extension

2.77 (0.45)

2.74 (0.49)

0.640

Flexion

1.44 (0.39)

1.42 (0.36)

0.559

5 Discussion The main findings of this study were that firstly, there was no significant difference in the relative peak torque between the dominant and non-dominant legs. According to the results of the study, when angular speed was 60°/s, the mean maximum muscular strengths (peak torque) of the dominant and non-dominant sides were, respectively, 2.77 ± 0.45 (extension), 1.44 ± 0.39 (flexion) and 2.74 ± 0.49 (extension), 1.42 ± 0.36 (flexion) showing no significant differences. Upon examination of the individual data, differences in the isokinetic knee strength ranged from –0.52 to +0.56 Nm kg−1 . However, this difference was not significantly different for group mean data. This finding may have been related to factors such as the influence of the nature of the Taekwondo sporting performance (Guan et al. 2018). The results gained from this study are in agreement with the study of Kim et al. (2015) that reported no significant differences between the two legs among Taekwondo athletes. Due to the insignificant difference in muscular strength between the dominant and non-dominant legs, we also learned that there is no significant relationship between leg preference and muscular strength asymmetry among Taekwondo athletes. Neither if the athletes were rightleg dominant nor left-leg dominant, there was insignificant difference in muscular strength asymmetry between the both legs. Differently from most isokinetic studies done previously, laterally dominant sport athletes such as soccer tend to convey

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significant strength deficits favoring the dominant leg (Daneshjoo et al. 2013). This was explained due to the sport’s asymmetric kinetic patterns and toleration bilateral bias while practicing the sport (Daneshjoo et al. 2013). Bilateral deficit is defined as the strength difference between opposite extremities. The results in this study showed that strength deficits among Taekwondo athletes were normal (less than 10%) at all angular velocities. In this study, differently from most isokinetic studies done previously, laterally dominant sport athletes such as soccer, futsal, handball, volleyball, and basketball tend to show abnormal strength deficits favoring the dominant leg (Daneshjoo et al. 2013). According to Iga et al. mentioned in Daneshjoo et al. (2013), soccer players almost never use equal legs with equal emphasis thus leading to hemispheric dominance that might further be a possible cause for deficit abnormality (Daneshjoo et al. 2013). Factors such as frequent use and task complexity were also discussed to be a contributing factor leading toward bilateral preference. Differently from Taekwondo, a non-laterally dominant sport, the athletes were required to possess equal strength and control on both sides of their lower extremities (Guan et al. 2018) thus helping to avert hemispheric dominance of the brain on neither side significantly. Difference in muscular strength between the dominant and non-dominant legs that were within the 10% range corresponds to the normal range. The results in this study showed that Taekwondo athletes in this study possess a balanced overall ratio of interlimb muscular strength ranged between −5.6 and 8.18% which did not correspond to increased risk of sports injury. In a recent study done by Yilmaz et al. (2021), Taekwondo kyorugi athletes also showed no significant bilateral asymmetry in lower limb muscular strength in all angular velocities and a balanced overall mean ratio of 2.9% of bilateral asymmetry index. Inversely, demonstration Taekwondo athletes conveyed more than 10% of bilateral asymmetry index which were considered as a direct cause of musculoskeletal injury (Ryu and Lee 2021). Higher bilateral asymmetries might also cost an athlete’s sporting performance as it by proxy signifies higher dispersion of impulse and maximal power (Menzel et al. 2012). Balanced muscular strength and endurance between the dominant and non-dominant legs were explained to be maintained during dynamic rhythm of Taekwondo kicking (Kim et al. 2015). These findings also suggest that Taekwondo training methods effectively involved the non-dominant foot without being shifted to the dominant foot. Thus, it is considered as beneficial to allow the athletes to score with both the dominant and non-dominant legs and positively affects steps that might help the body to move rapidly (Kim et al. 2015). Secondly, this study found an agreement between self-reported and observed leg preferences among Taekwondo athletes. Only one subject declared left-leg dominance and completed the ball kick task using right leg. The leg pronounced as dominant leg was the leg decided to kick a ball as postulated in a study done by Van Melick et al. (2017). According to Van Melick et al. (2017), the ball kick task was the most reliable test to rule out leg dominance among athletic population. This was discussed as the specific task is an automatically performed task, with no or a minor motor learning effect, most related to majority athletes’ daily lives and able to provide a

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better agreement (Van Melick et al. 2017), however have never been rectified on Taekwondo athletes as resolved in this current study. In conclusion, the finding of this study suggests that there was no significant relationship between leg preference and bilateral asymmetry among Taekwondo athletes. We also learned that compulsively, Taekwondo athletes do not exhibit significant bilateral asymmetry. Finally, this study found that there is an agreement between self-reported and observed leg preferences among Taekwondo athletes using the ball kick task. This study may have implications on determining the agreement between two methods of ruling out leg dominance. The ball kick task is a popular tool to assess leg dominance among athletic population, and we validated that it is applicable on Taekwondo athletes. Linearly from other studies, this study authenticated that Taekwondo athlete has no significant bilateral lower leg strength asymmetry due to the nature and demand of the sport. The future research should include ipsilateral strength ratio to focus and discover its effect on injury risk and sporting performance among Taekwondo athletes.

References Abd Rahman NA, Shaharudin S (2018) Comparison of skills and lower limb biomechanics of female futsal players at collegiate and club levels. Malaysian J Movement Health Exerc 7(2). https:// doi.org/10.15282/mohe.v7i1.245 Atasoy M, Karabulut EO, Var L (2018) The research on the negative evaluation anxiety of taekwondo players by different variables*. Turk J Sport Exerc. https://doi.org/10.15314/tsed.466880 Daneshjoo A, Rahnama N, Mokhtar AH, Yusof A (2013) Bilateral and unilateral asymmetries of isokinetic strength and flexibility in male young professional soccer players. J Human Kinet 36:45–53. https://doi.org/10.2478/hukin-2013-0005 Frutuoso AS, Diefenthaeler F, Vaz MA, de la Rocha Freitas (2016) Lower limb asymmetries in rhythmic gymnastics athletes Górski M, Orysiak J (2019) Differences between anthropometric indicators and the impact force of taekwondo kicks performed with the dominant and non-ominant limb. J Biomed Human Kinet 11(1):193–197. https://doi.org/10.2478/bhk-2019-0027 Guan Y, Guo L, Wu N, Zhang L, Warburton DER (2018) Biomechanical insights into the determinants of speed in the fencing lunge. Eur J Sports Sci 18(2):201–208. https://doi.org/10.1080/ 17461391.2017.1414886 Guan Y, Bredin S, Taunton J, Jiang Q, Wu L, Kaufman K, Wu N, Warburton D (2020) Bilateral difference between lower limbs in children practicing laterally dominant vs. non-laterally dominant sports. Eur J Sport Sci, pp 1–9. https://doi.org/10.1080/17461391.2020.1814425 Kim H-B, Jung H-C, Song J-K, Chai J-H, Lee E-J (2015) A follow-up study on the physique, body composition, physical fitness, and isokinetic strength of female collegiate taekwondo athletes. J Exerc Rehabil Menzel H-J, Chagas MH, Szmuchrowski LA, Araujo SRS, Andrade AGPD, Jesus-Moraleida FRD (2012) Analysis of lower limb asymmetries by isokinetic and vertical jump tests in soccer players. J Strength Conditioning Res Promsri A, Haid T, Werner I, Federolf P (2020) Leg dominance effects on postural control when performing challenging balance exercises. Brain Sci 10(3). https://doi.org/10.3390/brainsci1003 0128

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Ryu S, Lee T-K (2021) Biomechanical parameters that may influence lower limb injury during landing in Taekwondo. Medicina Sliwowski R, Grygorowicz M, Hojszyk R, Jadczak L (2017) The isokinetic strength profile of elite soccer players according to playing position. PLoS ONE 12(7):e0182177. https://doi.org/10. 1371/journal.pone.0182177 Van Melick N, Meddeler BM, Hoogeboom TJ, Nijhuis-van der Sanden MWG, Van Cingel REH (2017) How to determine leg dominance: the agreement between self-reported and observed performance in healthy adults. PLoS One 12(12):e0189876. https://doi.org/10.1371/journal. pone.0189876 Var SM (2019) Examination of bilateral and unilateral isokinetic leg strengths of taekwondo athletes and boxers. J Educ Learn 8(1):272. https://doi.org/10.5539/jel.v8n1p272 Yilmaz AK, Mayda MH, Kabadayi M, Yilmaz C, Era˙Il S, Karaduman E, Bostanci Ö (2021) Correlation of bilateral and ipsilateral strength ratios with balance in female taekwondo athletes. Revista De Artes Marciales Asiáticas 16(2):67–79

Muhd Ithar Haziq A Master of Sports Science Student (Via Coursework). Level 1 Taekwondo Coach with C Level Coaching Licence Certified by the National Coaching Academy and Taekwondo Malaysia.

Coaches’ Needs Satisfaction, Psychological Needs Thwarting and Motivation in Coaching Chin Ngien Siong, Teo Boon Sian, and Voon Mui Yee

Abstract The purpose of the study was to examine the basic needs satisfaction, psychological need thwarting and motivation among coaches in Sarawak, Malaysia. The participants were 251 coaches (194 male and 57 female) aged 18–57 years old (2.26 ± .93) whose coaching ranged from school to national level. The Basic Need Satisfaction at Work Scale for Coaches (BNSWSC), Psychological Need Thwarting Scale (PNTS) and Coach Motivation Questionnaire (CMQ) were used. Descriptive analysis, independent-samples t-test, one-way ANOVA and two-way ANOVA were utilized. The independent-samples t-test revealed significant difference between gender for relatedness, t = 2.37, p = 0.019. Besides, the one-way ANOVA revealed significant difference between age groups for intrinsic, p = 0.013. The one-way ANOVA also revealed significant difference between ethnicities for a motivation, p = 0.009. Two-way ANOVA revealed the main effect of gender was significant for relatedness, p = 0.03. Whereas, two-way ANOVA revealed the main effect of coaching level was significant for competence, p = 0.034, intrinsic motivation, p = 0.01, integrated regulation, p = 0.001, and identified regulation, p = 0.005. There was significant interaction between Gender × Coaching Level for competence, p = 0.041, relatedness, p = 0.006, intrinsic motivation, p = 0.021, and integrated regulation, p = 0.038. The findings provide deeper insight into the motivational underlying mechanism in coaching with effective strategies to satisfy the psychological needs of the coaches through strengthening of the environmental factors which can facilitate, support and sustain the coaching platform. Keywords Coaches · Needs satisfaction · Needs thwarting · Motivation

C. N. Siong (B) · T. B. Sian Department of Physical Education and Health, Institute of Teacher Education Batu Lintang Campus, Kuching, Sarawak, Malaysia e-mail: [email protected] V. M. Yee SK Gunong Ngeli, Simunjan, Sarawak, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_28

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C. N. Siong et al.

1 Introduction Coaches played a critical role in coaching, influencing, and encouraging athletes to accomplish and flourish at their highest levels of performance and to attain their full potential (Short and Short 2004). The amount of expectations of the athletes’ performance in terms of success and failures can affect and influence the motivation, behaviours and psychological well-being of the coaches in order to meet the ongoing demands of competitive sports. With the growing demands and pressure of the competitive sporting environment on the coaches which possess an instrumental role in the performance out- comes had influenced their satisfaction towards coaching. Coaches spend a lot of time on the field or court with their players, therefore analysing their behavioural motivation would help them contribute positively and effectively towards their goals. As a result, the construct of coaches’ fundamental need fulfilment may be useful in gaining understanding of how coaches should operate and grow, as well as examining the motivating capability of organisational elements. The self-determination theory (SDT: 2) used the Basic Psychological Need Theory (BPNT; 3) to anticipate variations in psychological and physical well-being by focusing on three psychological needs: autonomy, competence, and relatedness (Deci et al. 2001a). According to BPNT, if the situation encourages the support of the three psychological needs, one’s is more likely to feel the fulfilment needs. (Edmunds et al. 2006) stated that environment which satisfy the fundamental psychological needs would favour one’s satisfaction with higher motivation, enjoyment and satisfaction towards the activity. However, these requirements to cope are being thwarted by a variety of maladaptive coping behaviours (Olafsen et al. 2017). When coaches are satisfied with their needs, they are more likely to be motivated to perform efficiently and autonomously through their training and management of the programs and athletes (Nurhasni et al. 2019). According to literature, basic need satisfaction has been linked to psychological functioning and the quality of connections with other coaches and players, according to literature. (Abós et al. 2018) stated that more supportive autonomous behaviour in their decision-making and interest in coaching would arise from the effect of BPNT satisfaction. As the level of, dissatisfaction arised from frustration and obstruction of the psychological needs, it might probably lead to thwarting in the form of sub-optimal development and poor health (Bartholomew et al. 2014). Moreover, understanding how to inspire coaches to concentrate their needs and motivation to their performance, it is vital to concentrate on antecedents of psychological need thwarting so that they may be regulated to lessen turnover intention. Presently, no studies have examined basic needs satisfaction, thwarting and motivation among coaches which shows a need to understand the role of these constructs in motivation that can increase the field of literature. The relevance of motivational components of coaches’ satisfaction and psychological thwarting influence in the sports environment will fill a gap in the coaching research in Malaysia. This study aimed to examine coaches’ needs satisfaction, psychological needs thwarting and motivation in coaching.

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2 Methods 2.1 Participants and Procedure The participants comprised of coaches from various levels and sports, and actively coaching in Sarawak, Malaysia. Their informed consent to participate via online survey Google Form were obtained voluntarily, anonymity and confidentiality were guaranteed prior to the study. Upon the approval of ethics research committee of the Institute of Education Batu Lintang Campus, the study was carried accordingly. The participants were 251 coaches, comprising of 194 (77.3%) males and 57 (22.7%) females aged 18 to 57 years old (2.26 ± 0.93). In terms of ethnicity, a higher proportion of participants were Native (34.3%), followed by Malay (33.5%), Chinese (23.9%) and others (8.4%), respectively. Based on the coaching level, the majority of the participants were at school level with a total of 89, followed by state level at 68, division level at 31, district level at 27, national level at 22 and others at 14, respectively. 79.3% had 1–9 years of experience as a coach while 15.1% had 10– 19 years of experience and 5.6% had 20–29 years of experience. The demographics of the participants are presented in Table 1.

2.2 Measure The Basic Need Satisfaction at Work Scale for Coaches (BNSWSC; 9) was used to measure the degree of needs satisfaction among the coaches. The BNSWSC was formed by 12 items, 3 subscales which were autonomy (4 items; e.g., “I feel like I can pretty much be myself at work”), competence (3 items; e.g., “People at work tell me I am good at what I do”) and relatedness (5 items; e.g., “I really like the people I work with”). Items are rated on a 7-point Likert scale, ranging from 1 (Not true at all) to 7 (Very true). The subscales demonstrated high internal consistency ranging from 0.75 to 0.82 with the overall reliability of 0.92. The Psychological Need Thwarting Scale (PNTS; 10) was used to assess the degree of psychological need thwarting among athletes. The 12-items PNTSC comprised of 3 subscales with 4 items each, which are autonomy (e.g., “I feel pushed to behave in certain ways”), competence (e.g., “My PE teachers make PE class interesting experience for me”) and relatedness (e.g., “I feel others can be dismissive of me”). Items are rated on a 7-point Likert scale, ranging from 1 (Strongly disagree) to 7 (Strongly agree). The subscales demonstrated high internal consistency ranging from 0.89 to 0.91 with the overall reliability of 0.94. The Coach Motivation Questionnaire (CMQ; 11) was used to measure six forms of motivation. The WEMWBS consisted of 22-items that measured 6 subscales which were intrinsic (4 items; e.g., “Because I enjoy the effort I invest”), integrated (3 items; e.g., “Because coaching is fundamental to who I am”), identified (3 items; e.g., “Be- cause it is moving me toward my personal goals”), introjected (4 items;

350 Table 1 Demographic characteristics of the 251 participants

C. N. Siong et al. Characteristics Frequency (F) Percentage (%)

M (SD)

Gender

1.23 (0.42)

Male

194

77.3

57

22.7

18–27

56

22.3

28–37

101

40.2

38–47

66

26.3

48–57

28

11.2

Malay

84

33.5

Chinese

60

23.9

Native

86

34.3

Others

21

8.4

Female Age

2.26 (0.93)

Ethnicity

2.18 (0.99)

Coaching level

2.80 (1.62)

School

89

35.5

District

27

10.8

Division

31

12.4

State

68

27.1

National

22

8.8

Others

14

5.6

199

79.3

10–19

38

15.1

20–29

14

5.6

Years as a coach 1–9

1.26 (0.55)

e.g., “Because I feel responsible for the athletes’ performance”), external (4 items; e.g., “To be re- spected by others”), and amotivation (4 items; e.g., “I often think my coaching efforts are a waste of time”). Items are rated on a 7-point Likert scale, ranging from 1 (Strongly disagree) to 7 (Strongly agree). The subscales demonstrated high internal consistency ranging from 0.68 to 0.91 with the overall reliability of 0.87.

2.3 Data Analysis The Statistical Package for the Social Science (SPSS) 27.0 was utilised to analyse the data. The descriptive statistics was used to analyze the demographic variables of the participants. The independent sample t-tests, one-way Anova and two-way ANOVA

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was used to examine the gender, age groups and coaching levels of the BNSWSC, PTNS, and CMQ variables.

3 Results Table 1 shows the demographic characteristics of the participants. A total of 251 par ticipants were involved in this study, 194 (77.3%) males and 57 (22.7%) females. The age groups categories showed that 56 (22.3%) of the participants were 18–27 years old, 101 (40.2%) were 28–37 years old, 66 (26.3%) were 38–47 years old and 28 (11.2%) were 48–57 years old. In terms of ethnicity, the Native formed the largest percentage with 34.3%, followed by Malay (33.5%), Chinese (23.9%) and others (8.4%). Based on the coaching level, the majority of the participants were at school level (35.5%), followed by state level (27.1%), division level (12.4%), district level (10.8%), national level (8.8%) and others (5.6%), respectively. A total of 199 (79.3%) had 1–9 years of experience as a coach, while 15.1% had 10–19 years of experience and 5.6% had 20–29 years of experience. Table 2 shows the mean, standard deviation and reliability of BNSWSC, PNTS and CMQ. For BNSWSC, competence (5.81 ± 0.8) was the most essential factor that influenced the needs satisfaction among the coaches, followed by relatedness (5.79 ± 0.85) and autonomy (5.63 ± 0.86). The overall BNSWSC and subscales revealed high reliability of 0.92, 0.75, 0.788, and 0.82, respectively. For PNTS, competence (3.70 ± 1.55) was the most crucial construct that influenced the athletes’ degree of psychological need thwarting, followed by autonomy (3.55 ± 1.44) and relatedness (2.99 ± 1.49). The overall PNTS and subscales revealed high internal consistency of 0.94, 0.90, 0.89, and 0.91, respectively. For CMQ, identified (6.06 ± 0.93) was the most vital factors that influenced the coaches’ motivation, followed by intrinsic (5.91 ± 0.94), integrated (5.91 ± 1.00), introjected (5.77 ± 0.97), external (4.67 ± 1.53) and amotivation (3.10 ± 1.66). The overall CMQ and subscales also demonstrated high reliability ranging from 0.68 to 0.91. Table 3 shows the independent-samples t-test of BNSWSC, PNTS and CMS based on gender. For BNSWS, results revealed no significant difference between gender for autonomy, p = 0.39, competence, p = 21, and relatedness, p = 0.51. For PNTS, results revealed no significant difference between gender for autonomy, p = 0.08, and competence, p = 11. However, there was significant different between gender for relatedness, p = 0.019. The male rated 0.46 point higher than female. For CMQ, results revealed no significant difference between gender for intrinsic, p = 0.11, integrated, p = 0.07, identified, p = 0.15, interjected, p = 0.06, external, p = 0.06, and amotivation, p = 0.31. Table 4 shows the one-way ANOVA of BNSWSC, PNTS and CMQ based on age groups. For BNSWS, results revealed no significant difference between age groups for autonomy, p = 0.21, competence, p = 0.32, and relatedness, p = 0.22. For PNTS, results revealed no significant difference between age groups for autonomy, p = 0.51, competence, p = 0.35, and relatedness, p = 0.37. For CMQ, results revealed

352

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Table 2 Mean, standard deviation and reliability for BNSWSC, PNTS and CMQ Variables

M

α

SD

BNSWSC

0.92

Autonomy

5.63

0.86

0.75

Competence

5.81

0.88

0.78

Relatedness

5.79

0.85

0.82

Autonomy

3.55

1.44

0.90

Competence

3.70

1.55

0.89

Relatedness

2.99

1.49

0.91

Intrinsic

5.91

0.94

0.87

Integrated

5.91

1.00

0.91

Identified

6.06

0.93

0.88

Introjected

5.77

0.97

0.68

External

4.67

1.53

0.89

Amotivation

3.10

1.66

0.91

PNTS

0.94

CMQ

0.87

Table 3 Independent T-Test of BNSWSC, PNTS and CMQ based on gender Variables

Male

Female

t-test

M

SD

M

SD

t

df

p

Autonomy

5.65

0.87

5.54

0.82

0.86

249

0.39

Competence

5.85

0.89

5.68

0.84

1.26

249

0.21

Relatedness

5.81

0.84

5.72

0.87

0.66

249

0.51

Autonomy

3.63

1.50

3.29

1.20

1.75

112.54

0.08

Competence

3.78

1.54

3.41

1.56

1.60

249

0.11

Relatedness

3.09

1.56

2.63

1.20

2.37

116.33

0.019*

Intrinsic

5.97

0.94

5.74

0.96

1.62

249

0.11

Integrated

5.97

1.00

5.70

1.00

1.82

249

0.07

Identified

6.10

0.94

5.90

0.87

1.46

249

0.15

Introjected

5.83

0.93

5.56

1.07

1.90

249

0.06

External

4.76

1.54

4.32

1.47

1.91

249

0.06

Amotivation

3.16

1.72

2.90

1.45

1.03

249

0.31

BNSWSC

PNTS

CMQ

*p < 0.05

Coaches’ Needs Satisfaction, Psychological Needs Thwarting …

353

Table 4 One-way ANOVA of BNSWSC, PNTS and CMQ based on age groups Variables

18–27

28–37

38–47

48–57

F(3, 247)

p

0.90

1.52

0.21

0.93

1.18

0.32

6.03

0.83

1.49

0.22

1.43

3.59

1.85

0.78

0.51

3.87

1.53

3.96

1.95

1.11

0.35

3.14

1.35

3.17

1.91

1.05

0.37

0.98

5.80

0.96

6.35

0.79

3.64

0.013*

1.04

5.87

0.98

6.20

0.76

0.91

0.44

6.05

0.95

6.02

0.99

6.44

0.70

1.97

0.12

1.00

5.73

1.02

5.65

0.91

6.21

0.76

2.42

0.07

1.39

4.52

1.51

4.46

1.50

4.66

1.84

2.50

0.06

1.65

2.82

1.62

3.11

1.50

3.42

2.06

1.97

0.12

M

SD

M

SD

M

SD

M

SD

Autonomy

5.47

0.85

5.66

0.83

5.59

0.89

5.88

Competence

5.73

0.84

5.81

0.88

5.77

0.88

6.10

Relatedness

5.74

0.81

5.84

0.87

5.65

0.84

Autonomy

3.42

1.37

3.46

1.36

3.77

Competence

3.72

1.54

3.50

1.43

Relatedness

3.09

1.44

2.79

1.48

Intrinsic

5.69

0.85

5.99

Integrated

5.85

1.05

5.89

Identified

5.93

0.91

Introjected

5.77

External

5.14

Amotivation

3.42

BNSWSC

PNTS

CMQ

*p < 0.05

significant different between age groups for intrinsic, p = 0.013. Post-hoc Tukey adjusted comparisons for intrinsic indicated that age group of 48–57 was significantly higher than age group of 18–27, µ = 0.66, p = 0.013, and age group of 38–47, µ = 0.55, p = 0.048. However, results revealed no significant difference between age groups for integrated, p = 0.44, identified, p = 0.12, introjected, p = 0.07, external, p = 0.06, and amotivation, p = 0.12. Table 5 shows the one-way ANOVA of BNSWSC, PNTS and CMS based on ethnicity. For BNSWS, results revealed no significant difference between ethnicity for autonomy, p = 0.92, competence, p = 0.32, and relatedness, p = 0.97. For PNTS, results revealed no significant difference between age groups for autonomy, p = 0.85, competence, p = 0.23, and relatedness, p = 0.17, For CMQ, results revealed no significant different between age groups for intrinsic, p = 0.24, integrated, p = 0.40, identified, p = 0.65, introjected, p = 0.43, external, p = 0.51. Conversely, there was significant different be- tween ethnicity for amotivation, p = 0.009. Post-hoc Tukey adjusted comparisons for amotivation indicated that the mean score for Malay rated 0.73 point higher than the Chinese, p = 0.041. Table 6 shows the two-way ANOVA for BNSWSC, PNTS and CMQ based on gender and age groups. For BNSWSC, the between-subjects ANOVA for autonomy revealed that there was no significant main effect of gender, p = 0.78, and age groups, p = 0.48. Besides, there was no significant interaction between gender × age on autonomy, p = 0.71. The between-subjects ANOVA for competence revealed that

354

C. N. Siong et al.

Table 5 One-Way ANOVA of BNSWSC, PNTS and CMQ based on Ethnicity Variables

Ethnicity

F

p

5.74 (0.99)

0.16

0.92

5.87 (1.05)

1.18

0.32

5.85 (0.92)

0.08

0.97

0.27

0.85

Malay

Chinese

Native

Others

Autonomy

5.59 (0.85)

5.63 (0.79)

5.63 (0.90)

Competence

5.69 (0.91)

5.96 (0.78)

5.82 (0.86)

Relatedness

5.76 (0.88)

5.78 (0.79)

5.80 (0.85)

BNSWSC

PNTS Autonomy

3.55 (1.41)

3.43 (1.32)

3.64 (1.48)

3.49 (1.79)

1.46

0.23

Competence

3.88 (1.45)

3.42 (1.43)

3.80 (1.61)

3.38 (1.92)

1.70

0.17

Relatedness

3.28 (1.60)

2.75 (1.18)

2.90 (1.53)

2.89 (1.63)

1.70

0.17

Intrinsic

5.82 (0.98)

5.93 (0.89)

5.90 (0.93)

6.30 (0.97)

1.43

0.24

Integrated

5.96 (1.01)

5.80 (1.09)

5.87 (0.95)

6.21 (0.93)

0.99

0.40

Identified

6.02 (0.95)

6.06 (0.88)

6.03 (0.93)

6.30 (1.02)

0.54

0.65

Introjected

5.85 (0.93)

5.60 (1.13)

5.82 (0.87)

5.71 (1.02)

0.92

0.43

External

4.85 (1.69)

4.65 (1.52)

4.54 (1.34)

4.04 (1.70)

0.78

0.51

Amotivation

3.45 (1.78)

2.71 (1.39)

3.21 (1.64)

2.36 (1.61)

3.96

0.009*

CMQ

*p < 0.05

there was no significant main effect of gender, p = 0.39, ηp2 = 0.003, and age groups, p = 0.53. Further-more, there was no significant interaction between gender × age on competence, p = 0.72. The between-subjects ANOVA for relatedness revealed that there was no significant main effect of gender, p = 0.95, and age groups, p = 0.39. Next, there was no significant interaction between gender × age on relatedness, p = 0.21. For PNTS, the between-subjects ANOVA for autonomy revealed that there was no significant main effect of gender, p = 0.12, and age groups, p = 0.98. Besides, there was no significant interaction between gender × age on autonomy, p = 0.60. The between-subjects ANOVA for competence revealed that there was no significant main effect of gender, p = 0.17, and age groups, p = 0.61. Likewise, there was no significant interaction between gender × age on competence, p = 0.56. The betweensubjects ANOVA for relatedness revealed that there was significant main effect of gender, p = 0.03, but no significant main effect of age groups, p = 0.48. Moreover, there was no significant interaction between gender × age on relatedness, p = 0.28. Post-hoc Bonferroni adjusted comparisons for relatedness indicated that male rated 0.60 point higher than female, p = 0.03. For CMQ, the between-subjects ANOVA for intrinsic revealed that there was no significant main effect of gender, p = 0.71, and age groups, p = 0.08. Besides, there was no significant interaction between gender × age on intrinsic, p = 0.17. The between-subjects ANOVA for integrated revealed that there was no significant main effect of gender, p = 0.32, and age groups, p = 0.65. Next, there was no significant interaction between gender × age on integrated,

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p = 0.30. The between-subjects ANOVA for identified revealed that there was no significant main effect of gender, p = 0.70, and age groups, p = 0.23. Similarly, there was no significant interaction between gender × age on identified, p = 0.42. The between-subjects ANOVA for introjected revealed that there was no significant main effect of gender, p = 0.52, and age groups, p = 0.11. Additionally, there was no significant interaction between gender × age on introjected, p = 0.43. The betweensubjects ANOVA for external revealed that there was no significant main effect of gender, p = 0.42, and age groups, p = 0.06. Furthermore, there was no significant interaction between gender × age on external, p = 0.31. The between- subjects ANOVA for amotivation revealed that there was no significant main effect of gender, p = 0.52, and age groups, p = 0.18. Lastly, there was no significant interaction between gender × age on amotivation, p = 0.85. Table 7 shows the two-way ANOVA for BNSWSC, PNTS and CMQ based on gender and coaching level. For BNSWSC, the between-subjects ANOVA for autonomy revealed that there was no significant main effect of gender, p = 0.31, and coaching level, p = 0.19. Besides, there was no significant interaction between gender × coaching level on autonomy, p = 0.10. The between-subjects ANOVA for competence revealed that there was no significant main effect of gender, p = 0.58, but significant main effect of coaching level, p = 0.034. Furthermore, there was significant interaction between gender × coaching level on competence, p = 0.041. The between-subjects ANOVA for relatedness revealed that there was no significant main effect of gender, p = 0.20, and coaching level, p = 0.25. However, there was significant interaction between gender × coaching level on relatedness, p = 0.006. For PNTS, the between-subjects ANOVA for autonomy revealed that there was no significant main effect of gender, p = 0.22, and coaching level, p = 0.23. Next, there was no significant interaction between gender × coaching level on autonomy, p = 0.07. The between-subjects ANOVA for competence revealed that there was no significant main effect of gender, p = 0.07, and coaching level, p = 0.20. Likewise, there was no significant interaction between gender × coaching level on competence, p = 0.12. The between-subjects ANOVA for relatedness revealed that there was no significant main effect of gender, p = 0.31, and coaching level, p = 0.18. Similarly, there was no significant interaction between gender × coaching level on relatedness, p = 0.23. For CMQ, the between-subjects ANOVA for intrinsic revealed that there was no significant main effect of gender, p = 0.98, whereas significant main effect of coaching level, p = 0.01. Besides, there was significant interaction between gender × age on intrinsic, p = 0.021. The between-subjects ANOVA for integrated revealed that there was no significant main effect of gender, p = 0.94, yet significant main effect of coaching level, p = 0.001. Furthermore, there was significant interaction between gender × age on integrated, p = 0.038. The between-subjects ANOVA for identified revealed that there was no significant main effect of gender, p = 0.85, but significant main effect of coaching level, p = 0.005. Moreover, there was no significant interaction between gender × age on identified, p = 0.06. The between-subjects ANOVA for introjected revealed that there was no significant main effect of gender, p = 0.77, and coaching level, p = 0.05. Next, there was no significant interaction between gender × age on introjected, p = 0.26. The between-subjects ANOVA for

5.89

5.84

Relatedness

3.83

3.14

Competence

Relatedness

6.00

6.14

5.88

4.77

3.23

Integrated

Identified

Introjected

External

Amotivation

*p < 0.05

5.99

Intrinsic

CMQ

3.63

Autonomy

PNTS

5.67

Competence

3.03

4.55

5.77

6.07

5.82

5.93

2.54

3.43

3.21

5.83

5.75

5.62

0.42

0.65

0.42

0.14

0.98

0.14

4.74

1.88

2.38

0.004

0.75

0.08

0.52

0.42

0.52

0.70

0.32

0.71

0.03*

0.17

0.12

0.95

0.39

0.78

3.37

4.99

5.71

5.91

5.82

5.65

3.12

3.77

3.44

5.64

5.64

5.46

2.79

4.39

5.62

5.96

5.78

5.88

2.70

3.41

3.41

5.81

5.78

5.61

28–37

18–27

p

Age Groups (AG)

F(1, 243)

M

F

Gender (G)

Autonomy

BNSWSC

Variables

Table 6 Main-effect of gender versus age groups for BNSWSC, PNTS and CMQ

2.88

4.24

5.67

6.09

5.97

5.92

2.74

3.62

3.50

5.79

5.83

5.66

38–47

3.51

5.01

6.31

6.47

6.08

6.39

2.79

3.72

3.32

6.08

6.02

5.85

48–57

1.66

2.48

2.03

1.46

0.56

2.30

0.82

0.61

0.06

1.01

0.74

0.83

F(3, 243)

G versus AG

0.18

0.06

0.11

0.23

0.65

0.08

0.48

0.61

0.98

0.39

0.53

0.48

p

0.26

1.20

0.92

0.94

0.30

1.69

1.29

0.69

0.62

1.51

0.72

0.46

F(3, 243)

0.85

0.31

0.43

0.42

0.30

0.17

0.28

0.56

0.60

0.21

0.54

0.71

p

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external revealed that there was no significant main effect of gender, p = 0.59, and coaching level, p = 0.30. Likewise, there was no significant interaction between gender × age on external, p = 0.20. The between-subjects ANOVA for amotivation revealed that there was no significant main effect of gender, p = 0.70, and coaching level, p = 0.30. Similarly, there was no significant interaction between gender × age on amotivation, p = 0.48.

4 Discussion The findings supported BPSN’s theory that basic needs satisfaction and thwarting behaviours contributed to coach motivation while retaining a high degree of selfdetermination and intensity, through supporting autonomy in decision-making, valuing effort, and creating group cohesion. The desire for coaches’ relatedness, which meant that male coaches were more concerned with their utility values than female coaches, who were more concerned with intrinsic aspects of coaching. When compared to the female coaches, the male coaches were more likely to offer appreciation, encouragement, criticism, approbation, and feedback. This meant they were more likely to support the demands of competence, relatedness, and autonomy through progressive levels of engagement with peers in a learning setting, which would increase their motivation. Coaches who were able to satisfy their psychological needs were more likely to have autonomous motivation and interpersonal relatedness support rather than controlled motivation and a lack of interpersonal relatedness support as a result of disappointment and dissatisfaction (Rocchi and Pelletier 2018). The differences in ethnicties showed that coaches’ autonmous motivation for coaching were reduced to amotivation which could be due to poor environment such as absence of interpersonal support and pressure from higher authorities and other sources in terms of performance. For example, the lack of time from the athletes to train have led to their inability to perform and train accordingly which could have undermined in terms of their competence. Thus, the autonomy, relatedness and autonomy of needs have to be satisfied in order to increase the motivational behaviours of the coaches’ engagement, thus decreasing the needs thwarting in coaching. The limitation of this study is cross-sectional in nature utilising convenience sampling to reach to the coaches in Sarawak which limit the generalizability of the research as it is confined to one state. Thus, future studies need to be conducted in other states in Malaysia in order represent the overall population of coaches in Malaysia.

5.83

5.75

Relatedness

3.82

3.12

Competence

Relatedness

5.96

6.14

5.81

4.78

3.09

Integrated

Identified

Introjected

External

Amotivation

2.95

4.61

5.87

6.18

5.97

5.96

2.81

3.24

3.29

5.97

5.92

5.79

0.15

0.29

0.09

0.04

0.01

0.001

1.02

3.37

1.52

1.67

0.30

1.02

0.70

0.59

0.77

0.85

0.94

0.98

0.31

0.07

0.22

0.20

0.58

0.31

3.13

4.36

5.52

5.81

5.61

5.80

2.78

3.74

3.60

5.66

5.57

5.45

3.07

4.19

5.63

6.01

5.88

5.92

2.52

2.88

2.82

5.91

5.79

5.63

Note Sch = School, Dist = District, Div = Division, Nat = National *p < 0.05

5.96

Intrinsic

CMQ

3.65

Autonomy

PNTS

5.61

Competence

Dist

2.17

4.73

6.17

6.69

6.54

6.40

2.35

3.36

3.22

6.09

6.28

5.98

Div

Sch

p

Coaching level (CL)

F

M

F

Gender (G)

Autonomy

BNSWSC

Variables

Table 7 Main-effect of gender versus coaching level for BNSWSC, PNTS and CMQ

3.12

4.54

5.75

6.01

5.98

5.74

2.97

3.55

3.31

5.84

5.93

5.68

State

3.08

5.66

6.42

6.63

6.48

6.59

3.79

3.30

3.96

6.11

6.02

5.98

Nat

3.56

4.67

5.56

5.82

5.33

5.33

3.40

4.31

3.89

5.55

5.67

5.50

Other

1.23

1.22

2.26

3.41

4.12

3.10

1.55

1.47

1.40

1.34

2.46

1.51

F

0.30

0.30

0.05

0.005*

0.001*

0.01*

0.18

0.20

0.23

0.25

0.034*

0.19

p

G versus CL

0.91

1.47

1.30

2.16

2.39

0.01

1.38

1.78

2.10

3.34

2.36

1.99

F

0.48

0.20

0.26

0.06

0.038*

0.021*

0.23

0.12

0.07

0.006*

0.041*

0.10

p

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5 Conclusion The study extended present knowledge on the basic needs satisfaction, thwarting and motivation in coaching whereby coaches need to address the feeling of thwarting that could be due to controlling coaching curriculum, athletes’ time constraint, undervalue the perceptions of the coaches’ competence towards their performance. The appropriate sports authorities must be aware of the coaches’ work in order to revitalize the coaches’ personal progress in coaching by giving psychological requirements such as equitable support, opportunity, and acknowledgment.

References Abós A, Haerens L, Sevil J, Aelterman N, García-González L (2018) Teachers’ motivation in relation to their psychological functioning and interpersonal style: a variable- and person-centered approach. Teach Teach Educ 74:21–34 Bartholomew KJ, Ntoumanis N, Cuevas R, Lonsdale C (2014) Job pressure and ill-health in physical education teachers: the mediating role of psychological need thwarting. Teach Teach Educ 37:101–107 Deci EL, Ryan RM, Gagné M, Leone DR, Usunov J, Kornazheva BP (2001a) Need satisfaction, motivation, and well-being in the work organizations of a former Eastern Bloc country. Pers Soc Psychol Bull (in press) Edmunds J, Ntoumanis N, Duda J (2006) A test of self-determination theory in the exercise domain. J Appl Soc Psychol 36(9):2240–2265 Nurhasni MN, Mohamad FHH, Soh KG, Jane FS (2019) The relationship of coaching behaviour towards the motivation of football athletes in Malaysia sports’ school. Malaysian J Sport Sci Recreation 15(1):57–67 Olafsen AH, Niemiec CP, Halvari H, Deci EL, Williams GC (2017) On the dark side of work: a longitudinal analysis using self-determination theory. Eur J Work Organ Psy 26(2):275–285. https://doi.org/10.1080/1359432X.2016.1257611 Rocchi M, Pelletier L (2018) How does coaches’ reported interpersonal behavior align with athletes’ perceptions? Consequences for female athletes’ psychological needs in sport. Sport Exerc Perform Psychol 7:141–154. https://doi.org/10.1037/spy0000116 Short SE, Short M (2004) Coaches’ assessment of their coaching efficacy compared to athletes’ perceptions. Percept Mot Skills 99:729–736

Investigation of Coaching Effectiveness and Perfectionist in Sports: A Systematic Review Nurfatehah Ahmad Nasir, Ahmad Fikri Mohd Kassim, and Nurul Farha Zainuddin

Abstract The quality of relationships that coaches and athletes establish regulate the effectiveness of coaching, and obsessiveness is a personality trait outlined as striving for perfection and having astoundingly high-performance standards, as well as a propensity to overly, appraise one’s own or another’s actions. As a consequence, we sought to investigate the meta-analyses to gain further insight into coaching effectiveness and perfectionism. However, little is known about coaching effectiveness, and perfectionism is being studied throughout the following years. For data collection, the Preferred Reporting Items for Systematic Reviews (PRISMA) statements were used as a formal systematic review guideline. We identified relevant publications by using Web of Science and Scopus. The analysis is based on publications in English that were promulgated between the years 2017 and 2022 as well as the inclusion criteria. A systematic review focusing on evaluating papers on coaching effectiveness (n = 9) and perfectionism (n = 11) was being used to conspectus these studies. As a result, the findings systematically evaluate crosssectional observation-based studies, indicating that coaching effectiveness is essential for controlling athletes’ perfectionistic predilections during and/or when participating in any sporting activity. Analyses presented here suggest that coaching effectiveness significantly influences athlete performance and that athletes’ perfectionistic behaviours are one determinant of their eagerness to triumph. To conclude, implementing coaching effectiveness towards athlete performance is vital for athletes’ perfectionistic behaviours to achieve the desired efficiency whilst minimising athlete disappointment perfectionistic behaviours to achieve the desired efficiency whilst minimising athlete disappointment. Keywords Coaching effectiveness · Perfectionist · Athletes’ performance

N. A. Nasir · A. F. Mohd Kassim (B) · N. F. Zainuddin Faculty of Sports Science and Recreation, Universiti Teknologi MARA, Perlis Branch, Arau Campus, 02600 Arau, Perlis, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_29

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1 Introduction According to Jowett (2017), coaching is an interpersonal activity in which both a coach and an athlete must interact with one another; consequently, effective coaching is determined by the quality of relationships that coaches and athletes establish. Coaches will be able to balance depending on the performance of the athletes, whether they attained high standards or not; consequently, coaches will identify when striving begins to overwhelm and weaken critical areas that are deemed important for coach effectiveness. Coach motivation effectiveness, in particular, predicted athletes’ effort, devotion, and pleasure, technique effectiveness predicted players’ task self-efficacy, and character-building effectiveness predicted athletes’ prosocial behaviour (Kassim and Boardley 2018). Each successful coach–athlete connection fosters reciprocal trust, respect, and support (Jowett and Poczwardowski 2007). According to a study, a regression analysis of coach’s motivation effectiveness shows 29% and 41% based on variance in the UK and Malaysia athletes, indicating that athletes perceived their coach to be effective in developing psychological skills and motivational states of athletes when athletes have a stronger connection with coaches. Athletes are trained under the supervision of coaches in amazingly structured frameworks where sports provide a lucrative profession. Coaches that are deemed to be more effective at motivating athletes may indulge in more coaching activities dedicated to developing psychological abilities such as imagery, goal planning, and self-talk, which may help athletes to strengthen their confidence levels. Coaches are in charge of the athlete’s life and the sport that he or she has chosen. Nonetheless, they may display internal characteristics such as perfectionism (Fredrick et al. 2017) which may contribute to some young athletes having unreasonable expectations of themselves. Perfectionism is a personality trait described as striving for perfection and having exceedingly high-performance standards, as well as tendencies to overly, criticise one’s own or others’ actions (Frost et al. 1990; Flett and Hewitt 2002). Individuals who strive for perfection would define their self-worth primarily in terms of accomplishment, judging their experiences based on rigorous and overly demanding performance criteria, productivity, or success (Corrie and Palmer 2014). Healthy perfectionists show lower levels of burnout (Gotwals et al. 2012), and the development of healthy perfectionist orientations in youth athletes is correlated with exposure to heightened authoritative parenting (Sapieja et al. 2011). Perfectionistic athletes may train harder and for a longer period than non-perfectionistic athletes (Flett and Hewitt 2014). Some athletes’ training habits are prone to becoming obsessive and excessive (Madigan 2019). Each athlete has their own set of performance standards that serve as a guideline for them to meet their objectives. However, this has resulted in a disparity between an individual’s ideal self and their true self, which can have a negative impact on athletic performance (Ahmed et al. 2021).

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2 Methodology Search strategy: A systematic review seeks to discover, search, and synthesise literature linked to prior studies or research in a well-organised and transparent method that employs a replicable approach at each step. A systematic literature review (SLR) attempts to determine, ascertain, and integrate data from relevant articles to address the research question. We considered three different approaches to a literature review to be more specific guidelines for answering our research question: knowledge-building and theory-generating qualitative systematic review (FinfgeldConnett 2013), meta-aggregation (Hannes and Lockwood 2012), and scoping study (Arksey and O’Malley 2005). RAMESES: The authors used Realist and Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) guidelines as a mechanism of adhering to standard publication requirements to ensure that reviews contain the relevant and necessary information for users to assess the quality of a review (Wong et al. 2013). Metanarrative review is a relatively recent form of a systematic review that focuses on issues that have been conceived and investigated differently by multiple groups of scholars. RAMESES guidelines include (a) collated and summarised existing literature, (b) synthesising identification and evaluation of inclusion and exclusion criteria, and (c) the capacity to generate major databases of scientific literature in a brief period. Resources: Web of Science (WOS) and Scopus were chosen as preferred databases in this review as they are both well-known as prominent index systems of citations in publications. Web of Science is well-known as a database of transdisciplinary bibliographic citations and is a paid access platform for accessing various databases for reference and citation. Meanwhile, Scopus offers the world’s largest abstract and citation database, facilitating the easy identification of research based on scientific journals, conference proceedings, and books. These two databases were selected because of their dominance as the most favoured search engine database among researchers, which is significant for authors to optimise and ensure the quality of the articles being evaluated. Systematic review process (identification): Prior to the first stage of this metanarrative process, identification phases are being carried out in May 2022. This approach entailed identifying keywords from relevant sources such as dictionaries, thesaurus, keywords from existing literature, proposed synonyms keywords from Web of Science and Scopus, and similar phrases (see Table 1 and 2). This approach generated results from the selected database, including 51 (CE) and 72 (P) papers from Web of Science (WOS) and 69 (CE) and 19 (P) documents from Scopus (see Figs. 1 and 2). Screening process (inclusion and exclusion): Screening is a technique that identifies articles/journals based on a sampling frame that is examined to determine whether it is compatible with inclusion or exclusion criteria that the authors have determined. Eligibility, inclusion, and exclusion criteria were set throughout the screening process to recognise acceptable articles to be included in the evaluation. The first inclusion

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Table 1 Keywords and search strings for coaching effectiveness Databases

Keywords used

Web of Science TS = ((“coaching effectivenes*” OR “coaching effectiv*” OR “coaching efficac*” OR “coaching efficienc*” OR “coaching capabilit*” OR “coaching potenc*” OR “coaching powe*” OR “coaching competenc*” OR “coaching abilit*” OR “coaching adequanc*” OR “coaching performanc*”) AND (“spor*” OR “athlet*” OR “yout*”)) Scopus

TITLE-ABS-KEY ((“coaching effectivenes*” OR “coaching effectiv*” OR “coaching efficac*” OR “coaching efficienc*” OR “coaching capabilit*” OR “coaching potenc*” OR “coaching powe*” OR “coaching competenc*” OR “coaching abilit*” OR “coaching adequanc*” OR “coaching performanc*” AND “spor*” OR “athlet*” OR “yout*”))

Table 2 Keywords and search strings for perfectionists Databases

Keywords used

Web of Science

TS = ((“perfectionis*” OR “perfec*” OR “idealis*” OR “flawles*” OR “superlativ*” OR “faultles*” OR “utte*” OR “pristin*”) AND (“spor*” OR “athlet*” OR “yout*”))

Scopus

TITLE-ABS-KEY (“perfectionis*” OR “perfec*” OR “idealis*” OR “flawles*” OR “superlativ*” OR “faultles*” OR “utte*” OR “pristin*” AND “spor*” OR “athlet*” OR “yout*”)

criteria, which are based on the study’s timeframe, were chosen between 2017 and 2021. Following that, the writers determined an article journal with empirical data and others (review articles, chapters in books, and conference proceedings were omitted because they were not regarded as primary sources). Finally, as non-English language documents, language became one of the prior inclusion criteria in these studies (see Table 3). Eligibility and duplication exclusion: One procedure that identifies any repeating documents between the databases which have already been obtained is duplicate. As a result, the duplicate article process is critical in this entire selection criteria-based process. Thirty-one papers (coaching effectiveness) and 15 articles (perfectionist) were identified as duplicates and eliminated from studies. As a result, only 88 documents (CE) and 76 documents (P) were left for the eligibility procedure and were Table 3 Inclusion and exclusion criteria Criteria

Inclusion

Exclusion

Timescale

Between 2017 and 2021

0.05 using the ShapiroWilks test, and the result indicate the normality test was confirmed to be normal. A mixed model repeated measure two-way analysis of variance (ANOVA) was used to

Effect of Both Side up Ball and the Biodex Balance System Training …

391

Table 1 Five-week BOSU ball balance training program Week

Single leg balance Rotary squat with torso rotation with jump stick

Leap hold with compressions

Duration (s)

Rest (s)

Rep (s)

Rest (s)

Rep (s)

Rest (s)

5

10

10

20

30

10 each side 30 compression

40

2

5

20

10

25

30

15 each side 30 compression

40

3

5

30

10

30

30

20 each side 30 compression

40

4

5

40

10

35

30

25 each side 30 compression

40

5

5

50

10

40

30

30 each side 30 compression

40

1

Platform type

Rubber dome

Warm-up (min)

Note Rep: Repetition

Fig. 2 Example of Exercises for BBS Training (i) balancing/rebalancing and postural stability exercise with and without visual feedback, (ii) weight shift exercises

392

T. S. Han et al.

Table 2 Five-week Biodex balance system (BBS) training program Week Platform Warm-up (min) Balancing and stability level postural stability exercise with visual feedback

Balancing and Weight shift postural stability exercise exercise without visual feedback

Rep (s) Rest (s) Rep (s) Rest (s) Rep (s) Rest (s) 1

Static

5

3

10

3

10

2

40

2

6

5

3

10

3

10

2

40

3

8

5

3

10

3

10

2

40

4

10

5

3

10

3

10

2

40

5

12

5

3

10

3

10

2

40

Note Rep = repetition

determine the effect of the BOSU ball training and BBS training on static balance and dynamic balance against time (pre and post). A Tukey post-hoc analysis was used to determine pairwise difference. Values are presented as mean ± SD and statistical significance was set at p < 0.05. Effect size was calculated using Cohen’s d for t-tests being interpreted, as small ( and and and 0.9). The sample size was determined using the G Power and G*Power calculation software (version 3.1.9.7) matches to a similar study (Gusi et al. 2012), and the sample size calculated for this study is 20.

3 Results For static test, the results showed significant time effect (F 3, 88 = 103.4, p ≤ 0.0001) was observed in BOSU group (Fig. 3a, b). Percentage difference between post- and pre-test showed that BOSU training provided greater advantage (60%) compared to BBS (20%), although no statistical difference was found in post between groups. A very large effect size was detected post-test between BOSU and BBS (d = 0.81). While for dynamic test, both groups showed no improvements in between group (F 1, 44) = 0.6646, p = 0.4193) and for time factors (F 1, 44 = 9.075, p > 0.05). A small effect size was detected between post-test BOSU and BBS (d = 0.03).

4 Discussion The aim of this study was to compare 5 weeks of BOSU ball and BBS training program on static and dynamic balance among overweight sedentary young adults. The main results were BOSU had shown significant improvement in static balance

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Fig. 3 a The effect of BOSU ball training and BBS training on static balance measured using the Standing Stork Test. *denotes significant difference between pre- and post-test. b The effect of BOSU ball training and BBS training on dynamic balance measured using the Standing Stork Test. *denotes significant difference between pre- and post-test

(SST), however not in dynamic balance (FSST). While BBS had shown no significant improvement in both static and dynamic balance. It seems that longer duration intervention is needed to observe changes in dynamic balance. In addition, both training program place great emphasis on static balance component, hence, as expected, participants perform better in static test, and it is also possible that the balance tests administered are unable to reflect the changes in BBS training. The BOSU group showed significant increase in static balance, and this finding is similar to previous studies (Yaggie and Campbell 2006; Paterno et al. 2004). The 5-week intervention period is sufficient to elicit a proprioceptive change and improve static balance since, even a 4-week training had shown improvement (Yaggie and Campbell 2006). It is postulated that the BOSU ball training is sufficient to increase the muscular recruitment pattern in the ankle leading to improved postural control (Rozzi et al. 1999). In contrast, dynamic balance component showed no significant changes despite studies showing improvements in dynamic balance following BOSU ball training (Joshi et al. 2015; Myer et al. 2005). Two possible factors that may have influenced this observation; (i) types of training performed as a previous study used a multifaceted intervention with uses rapid change of direction and jumping exercises with balance training (Komi and Viitasalo 1977), the dynamic balance tests used (the aforementioned studies employed the Star Excursion Balance Test) which may be more sensitive in detecting dynamic balance changes (Olmsted et al. 2002; Plisky et al. 2006). In addition, BOSU training is not confined to a limited space compared to BBS, hence, demands greater control (proprioception; base of support, visual and vestibular systems), which translates to greater outcome (Ha et al. 2018). Previous studies have shown that individuals who are categorized as overweight have a reduced static postural control compared to their counterparts which are either normal weight or underweight (Ku et al. 2012; Colne et al. 2008). A suggestion by the previous study is to introduce a balance training intervention to counteract the loss of balance due to weight gain (Porto et al. 2012). Therefore, a training tool such as the BOSU ball which is easily accessible can be used as a countermeasure for the weight-induced loss of postural control. As clearly shown in this study, BOSU ball

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training is able to improve the static balance in this population as early as 5-week training. Meanwhile, BBS group showed no significant improvement in both static and dynamic balance tests, although previous studies have shown otherwise (El-Gohary et al. 2017; Gusi et al. 2012). These could be due to characteristics of the participants employed; here, young overweight sedentary adults, while in previous studies older adults and children with diplegia were employed. The primary goal of BBS training in previous studies was to reintroduce or improve proprioception deficit due to medical conditions, while in this study none of the participants reported having a lower body injury. Next, the training period may not be sufficient to induce significant balance changes in this study. Previous studies which showed improvements had employed a longer training period (>5 weeks) (El-Gohary et al. 2017; Gusi et al. 2012). It is speculated that 5 weeks of BBS training in this study was not sufficient to show changes. Another factor to consider is the physical difference between both devices, BOSU training is on a half circle dome, while the BBS a flat surface. The flat surface relies on the proprioceptive system feedback, while BOSU relies on somatosensory system feedback (Ha et al. 2018). Thus, the changes in proprioception may not be captured by the tests employed. Therefore, adding longer period of intervention and multiple tests to evaluate changes in both BOSU and BBS are recommended. Regarding practical application, the data of the study suggest that BOSU ball is a practical training tool which can improve static balance compared to BSS which may not be suitable for overweight collegiate males after 5 weeks of training, perhaps longer duration of intervention is required. BOSU ball is widely used conventionally in various types of training, such as stretching, rehabilitation, and muscular conditioning. Based on the findings, balance training on a BOSU ball provides an extra challenge and intensity compared to BBS. BOSU ball training may improve postural control and implement preventive measures against the loss of equilibrium from being in an overweight state. In summary, this is the first comparative study to investigate the effect of BOSU ball training and the BBS in improving balance. The main finding of this study is that BOSU ball training is able to improve static balance after 5 weeks of training for the overweight collegiate population. However, both trainings are not sufficient to elicit changes in dynamic balance, since both exercises place great emphasis on static component. Author Contributions Tan Shi Han: manuscript writing and preparation. Khong Teng Keen: result interpretation and overseeing the research. Ashril Yusof: manuscript writing and data analysis. All author read and approved the final version of the manuscript. Declarations The authors declares that they have no competing interest and have not received funding for this research.

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References Aras D, Kitano K, Phipps AM, Enyart MR, Akça F, Koceja DM et al (2018) The comparison of postural balance level between advanced sport climbers and sedentary adults. IJAEP 7(3):1–9 Clark KN (2004) Balance and strength training for obese individuals. Acsms Health Fit J 8(1):14–20 Colne P, Frelut ML, Peres G, Thoumie P (2008) Postural control in obese adolescents assessed by limits of stability and gait initiation. Gait Posture 28(1):164–169 Del Porto H, Pechak C, Smith D, Reed-Jones R (2012) Biomechanical effects of obesity on balance. Int J Exerc Sci 5(4):1 Dunsky A, Zeev A, Netz Y (2017) Balance performance is task specific in older adults. Biomed Res Int 2017:6987017 El-Gohary TM, Emara HA, Al-Shenqiti A, Hegazy FA (2017) Biodex balance training versus conventional balance training for children with spastic diplegia. J Taibah Univ Med Sci 12(6):534–540 Gioftsidou A, Malliou P, Pafis G, Beneka A, Godolias G, Maganaris CN (2006) The effects of soccer training and timing of balance training on balance ability. Eur J Appl Physiol 96(6):659–664 PubMed PMID: 16416322 Gusi N, Carmelo Adsuar J, Corzo H, Del Pozo-Cruz B, Olivares PR, Parraca JA (2012) Balance training reduces fear of falling and improves dynamic balance and isometric strength in institutionalised older people: a randomised trial. J Physiother 58(2):97–104 Ha SY, Han JH, Sung YH (2018) Effects of ankle strengthening exercise program on an unstable supporting surface on proprioception and balance in adults with functional ankle instability. J Exerc Rehabil 14(2):301–305 Hassinen M, Komulainen P, Lakka TA, Väisänen SB, Rauramaa R (2005) Associations of body composition and physical activity with balance and walking ability in the elderly. J Phys Act Health 2(3):298–306 Joshi N, Mahishale A, Motimath B (2015) Comparative study of 4 weeks of dynamic balance training program in collegiate football players: randomized clinical trial. J Evid Based Med Healthc 2(10) Komi PV, Viitasalo JT (1977) Changes in motor unit activity and metabolism in human skeletal muscle during and after repeated eccentric and concentric contractions. Acta Physiol Scand 100(2):246–254 Ku PX, Abu Osman NA, Yusof A, Wan Abas WA (2012) Biomechanical evaluation of the relationship between postural control and body mass index. J Biomech 45(9):1638–1642 Miller D (2013) Measurement by the physical educator why and how. McGraw-Hill Higher Education Myer GD, Ford KR, Palumbo JP, Hewett TE (2005) Neuromuscular training improves performance and lower-extremity biomechanics in female athletes. J Strength Cond Res 19(1):51–60 Olmsted LC, Carcia CR, Hertel J, Shultz SJ (2002) Efficacy of the star excursion balance tests in detecting reach deficits in subjects with chronic ankle instability. J Athl Train 37(4):501–506 Paterno MV, Myer GD, Ford KR, Hewett TE (2004) Neuromuscular training improves single-limb stability in young female athletes. J Orthop Sports Phys Ther 34(6):305–316 Plisky PJ, Rauh MJ, Kaminski TW, Underwood FB (2006) Star excursion balance test as a predictor of lower extremity injury in high school basketball players. J Orthop Sports Phys Ther 36(12):911–919 Rozzi SL, Lephart SM, Sterner R, Kuligowski L (1999) Balance training for persons with functionally unstable ankles. J Orthop Sports Phys Ther 29(8):478–486 Whitney SL, Marchetti GF, Morris LO, Sparto PJ (2007) The reliability and validity of the four square step test for people with balance deficits secondary to a vestibular disorder. Arch Phys Med Rehabil 88(1):99–104

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Winter DA, Patla AE, Frank JS (1990) Assessment of balance control in humans. Med Prog Technol 16(1–2):31–51 Yaggie JA, Campbell BM (2006) Effects of balance training on selected skills. J Strength Cond Res 20(2):422–428

The Effects of Foam Rolling on Flexibility and Hip Range of Motion Among Individuals with Different Body Mass Index (BMI) J. M. Wong, P. Y. Lian, K. Q. Chan, T. K. Khong, and A. Yusof

Abstract Foam rolling (FR) exercise, also known as self-myofascial release, is one of the most often utilized pre-exercise stretching methods in sports. It improves muscular functions and flexibility as well as reduces muscle fatigue and soreness during recovery. While performing a FR exercise, one uses one’s body weight to exert pressure on the roller. Despite body weight being a factor influencing the pressure exerted, there is no study that investigated whether BMI category would affect the outcomes of FR exercise. Hence, the objective of this study was to determine the effects of two-week of FR exercise on flexibility (Sit and Reach), hip range of motion (hROM), and comparing the outcomes between various BMI category. Twenty-four participants were recruited and assigned into groups based their BMI categories: underweight (UWT), normal weight (NWT), and overweight (OWT). The seat and reach distance and hROM were measured at baseline, acute effect (T 1 ) and after two-week training (T 2 ). The two-week intensive FR intervention showed significant improvements in flexibility (seat and reach; T 0 vs T 2 for NWT (p = 0.0031) and OWT (p = 0.0021)), and hROM measures (p < 0.05). Interestingly, the improvements observed following this two-week intervention are comparable to a reported four-week FR intervention program. In brief, higher BMI category (normal and overweight categories) could benefit more from FR exercise compared to underweight for flexibility and ROM. Keywords Foam rolling · Flexibility · Range of motion · Body max index

J. M. Wong · P. Y. Lian · T. K. Khong · A. Yusof (B) Universiti Malaya, 50603 Kuala Lumpur, Malaysia e-mail: [email protected] K. Q. Chan Tunku Abdul Rahman University College, 53300 Kuala Lumpur, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_31

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1 Introduction Foam rolling (FR) exercise is a form of myofascial release which promotes muscular function and flexibility, as well as reduces muscle fatigue and soreness. In recent years, it has become a popular tool in improving sports performance during training, competition, and recovery (Wiewelhove et al. 2019). During FR exercise, one applies one’s body weight on the roller to exert pressure on the soft tissues which stretches the underlying tissues (Pearcey et al. 2015). This causes a self-myofascial shift in the water content and increases pliability of the tissues which in turn increases range of motion (ROM) (Beardsley and Škarabot 2015). In addition, an adequate amount of mechanical pressure is necessary to stimulate the production of collagen-fiberproducing cells which in long run improves flexibility (Schleip 2003). Calisthenically, the pressure is dependent on one’s body weight, hence, the outcomes of FR exercise such as flexibility and ROM would hypothetically be afftected by BMI categories. Both acute and long term training of FR exercise have been shown to improve flexibility (Do and Yim 2018; Mohr et al. 2014; Sullivan et al. 2013). In general, two sessions of FR training per week for 8 weeks (Boguszewski et al. 2017), 5 weeks (Kiyono et al. 2020), and three times per week for 4 weeks Junker and Stöggl 2015) have been shown to improve flexibility and ROM. It appears that the effect of FR training is dose dependent whereby similar outcomes can be achieved by manipulating exercise volume and training duration. In the cited studies, (ROM) has been widely used to indicate improvement in flexibility as well as motor capacities (Shadmehr et al. 2009). Comparing to traditional static and dynamic exercises which are known to improve flexibility, FR has emerged as a simple method that is more effective (Behara and Jacobson 2017; Smith et al. 2018; Su et al. 2017). It is also easy and needs little time (less than 10 min) to execute, which is the objective of this study. A meta-analysis has pointed out that, although flexibility and ROM are improved following FR exercises, the pressure exerted varies between individuals (Wiewelhove et al. 2019). Since the outcomes of FR training is dependent upon the pressure exerted, individuals with different BMI would rationally exert different level of pressure which in turn influences the outcome measures. Hence, the objective of this study was to determine the effects of five sessions per week for two weeks of FR exercise on flexibility and ROM among individuals with different BMI categories. It is hypothesized that heavier body weight category would produce higher pressure, hence producing greater flexibility and ROM.

2 Methodology Study Design This study employed an experimental design where participants with different BMI categories went through the same FR exercise intervention. Sit and reach flexibility

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and hip ROM measurements were taken at baseline; T 0 , immediately after the first FR exercise session; T 1 , and at post-test; T 2 two weeks later (after 10 FR sessions). Participants Twenty-four sedentary to moderately active individuals consisting of 12 males and 12 females volunteered for the study. A convenience sampling technique was used using social media and email invitations. A sample size of 18 was obtained (bloated to 24) from GPower 3.1.9.2 software using the A Priori test under the F test family, where alpha error probability was set at 0.5, Power at 0.80, and effect size at 0.82 based on the meta-analysis of FR on ROM (Konrad et al. 2022). Participation inclusion consisted of: (a) healthy, (b) sedentary or moderately active based on the International Physical Activity Questionnaire (I-PAQ) scoring as these sample population would benefit most from the exercises prescribed, (c) free from any injury or disease that could affect flexibility (within six months prior to the study), and (d) ready for physical activity based on the Physical Activity Readiness Questionnaire (PAR-Q). According to the WHO BMI classification where BMI score of 0.05. A two-way analysis of variance (ANOVA) test (group × time) was conducted using repeated measures to identify significant interaction between the variables. Bonferroni’s post-hoc test was then conducted to determine the pair-wise differences between the variables. The p-value was set to p < 0.05, and data is presented as mean and standard deviation (Mean ± SD).

3 Results Participants’ Anthropometry The participants were assigned to underweight (UWT) (n = 8; height; 146.8 ± 54.07 cm; weight, 49.34 ± 8.26 kg; age, 22.13 ± 1.46 years; BMI, 17.51 ± 1.48 kg/m2 ), normal weight (NWT) (n = 8; height; 166.7 ± 6.62 cm; weight, 60.11 ± 6.62 kg; age, 22.13 ± 0.64 years; BMI, 21.60 ± 1.32 kg/m2 ) and overweight (OWT) (n = 8; height; 167.90 ± 8.04 cm; weight, 76.35 ± 10.07 kg; age, 21.50 ± 1.85 years; BMI, 26.99 ± 1.72 kg/m2 ) groups. See Table 1. Flexibility and Hip ROM Two-way ANOVA showed significant time effect (F 1.8, 37.9 = 6.6, P = 0.004), where 2 weeks of FR training is better than acute FR in SAT in underweight and normal weight groups, while in the overweight group, the 2-week training also produced better flexibility when compared to baseline (P < 0.05) (Fig. 3). Evidently, no between group difference was observed at T 0 . Meanwhile for hROM test, significant time effect was reported in all movements in both limbs (p < 0.05). Most changes were found after 2 week of FR intervention Table 1 Physical characteristics of participants according to their BMI groups, presented as Mean ± SD

UW (n = 8)

NW (n = 8)

OW (n = 8)

Age (years old)

22.13 ± 1.46

22.13 ± 0.64

21.50 ± 1.85

Weight (kg)

49.34 ± 8.26

60.11 ± 6.62

76.35 ± 10.07

Height (cm) BMI (kg/m2 )

146.8 ± 54.07 166.7 ± 6.62 17.51 ± 1.48

21.60 ± 1.32

167.90 ± 8.04 26.99 ± 1.72

UW underweight; NM normal weight; OW overweight

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Fig. 3 Sit and reach test results. **Significant difference (P < 0.05)

in all BMI categories (Table 2). For UWT, changes in hip adduction and internal rotation, for NWT, hip flexion/extension, hip abduction, and external rotation, while for OWT, hip flexion/extension internal/external rotation were found improved after 2 weeks.

4 Discussion This study showed that FR training consisting of ten sessions (five sessions per week) for two weeks has significantly improved flexibility and hROM in all BMI categories measured. It is worth noting that those in NWT and OWT categories benefited more than those in UWT. This is especially apparent in the sit and reach results. In addition, there were also concomitant improvements in hROM measures. It is also apparent that a two-week short-term high-volume FR training is more effective than an acute training, as flexibility and hROM improvements were seen in T 2 but not T 1 . The improvements in flexibility and hROM were significant among NWT and OWT group due to higher body weight contributed to an increased pressure exerted onto the muscle during FR exercise (Yoshimura et al. 2020). This could be attributed to an increase in mechanical pressure generated during FR causing an increase in mechanostimulation of the fascia which in turn increases the longitudinal extensibility of the muscle, thereby improving flexibility and ROM (Weerapong et al. 2005). On the other hand, for the UWT category, they may not have exerted sufficient pressure as well as having lesser pliable fascia (Tas et al. 2017) compared to NWT and OWT groups. Comparatively, FR could exert greater benefit on flexibility compared to stretching exercise where a six-week static stretching did not improve flexibility in individuals with different BMI categories (Cox 2021). It is suggestive that individuals in normal and obese BMI category could benefit from FR exercise compared to those in underweight BMI category.

T1

T2

20.69 ± 3.23

22.75 ± 3.78

23.56 ± 3.44

Hip 21.95 ± 2.81 adduction (L)

Hip 22.63 ± 4.07 adduction (R)

24.57 ± 5.87

24.00 ± 4.50

28.19 ± 6.88

Hip 26.44 ± 14.67 25.25 ± 17.81 27.13 ± 9.71 abduction (R)

23.69 ± 4.58

26.00 ± 7.68

Hip 27.50 ± 11.68 26.88 ± 11.92 26.94 ± 7.64 abduction (L)

27.44 ± 3.72

28.81 ± 6.28

26.50 ± 9.24

Hip 26.88 ± 6.45 extension (R)

29.50 ± 6.92

27.38 ± 7.41

28.50 ± 6.65

Hip 28.13 ± 8.05 extension (L)

25.69 ± 5.69

23.31 ± 5.43

30.75 ± 4.18

27.88 ± 5.57

30.06 ± 3.65

29.50 ± 3.65

26.94 ± 3.93

25.54 ± 4.52

27.13 ± 4.86

25.06 ± 7.55

41.44 ± 7.45*

27.35 ± 8.27

26.50 ± 6.43

25.13 ± 9.78

23.38 ± 3.24

23.94 ± 5.77

24.75 ± 3.39

24.13 ± 3.93

28.56 ± 10.84 29.81 ± 9.78

43.03 ± 10.94* 26.38 ± 8.49

32.56 ± 3.20*

29.86 ± 3.32

(continued)

24.80 ± 4.29

22.88 ± 2.59

29.88 ± 9.21

27.25 ± 9.33

26.13 ± 3.88

31.13 ± 2.97*

79.13 ± 10.87 86.63 ± 12.79 88.38 ± 17.68 77.00 ± 12.01 80.56 ± 11.55 90.69 ± 13.02* 78.00 ± 11.61 76.31 ± 16.53 89.94 ± 18.36*

T0

Overweight

Hip flexion (R)

T2

76.44 ± 21.40 93.56 ± 14.89* 74.31 ± 10.06 76.69 ± 10.74 93.19 ± 21.81*

T1

77.56 ± 11.94 82.38 ± 16.60 86.25 ± 14.43 76.69 ± 9.85

T0

Hip flexion (L)

Normal weight

T2

T0

T1

Underweight

Table 2 Hip ROM at all time points. Unit for all values is degree/°

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31.94 ± 5.88

30.06 ± 5.90

Hip external rotation (R)

different from T 0

34.88 ± 8.92

34.75 ± 7.86

Hip external rotation (L)

* Significantly

36.91 ± 8.32

36.69 ± 6.77

Hip internal rotation (R)

31.81 ± 7.97

35.06 ± 5.94

32.50 ± 6.55

33.38 ± 8.58

43.94 ± 8.28* 34.88 ± 8.49

32.94 ± 7.01

32.56 ± 8.95

31.75 ± 8.68

Hip internal rotation (L)

34.06 ± 2.77

Normal weight T0

T0

T2

T1

Underweight

Table 2 (continued)

33.00 ± 7.26

34.75 ± 6.95

36.94 ± 8.26

33.38 ± 6.61

T1

33.00 ± 2.56

40.56 ± 7.92*

36.25 ± 5.01

34.00 ± 6.36

T2

Overweight

34.06 ± 7.07

31.11 ± 8.25

29.63 ± 7.77

T1

38.50 ± 10.78 39.06 ± 5.54

35.63 ± 7.34

29.00 ± 8.04

29.69 ± 6.15

T0

38.69 ± 7.24

42.69 ± 4.01*

32.13 ± 8.17

34.88 ± 7.49

T2

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The improvements in flexibility and hROM in NWT and OWT are comparable to many studies that prescribed at least four-week of FR exercise for two to three times/week (Boguszewski et al. 2017; Kiyono et al. 2020; Hodgson et al. 2018; Junker and Stöggl 2015). In a review and meta-analysis (Konrad et al. 2022), it was suggested that at least a 4-week intervention is needed to observe changes in flexibility and ROM, interestingly, in this study a higher volume of FR training is proven viable, furthermore each training session only takes up a brief time (less than 10 min). In present study, a shorter period (2 weeks) with a higher training frequency (5 times/week) is sufficient to improve flexibility and ROM which suggests that these outcomes are dose dependent. Speculatively, a two-week of high volume FR training is sufficient to cause adaptation in Golgi Tendon Organ and muscle spindle allowing muscle fibers to stretch, unknot, and realign which consequently increase flexibility and ROM (Reid and McNair 2004). There are few limitations that need mentioning in this study. First, the data may only be applicable to collegiate age group who are sedentary to moderately active. A standard BMI category was used in this study for comparative reasons (with existing literature), hence the data may not be suitable for comparison with the Asian BMI category. Lastly, having a barometer (pressure) measurement would provide relevant information on the pressure exerted by body weight on the FR. In brief, a two-week of intensive (five sessions per week) FR training is sufficient to improve flexibility and hROM. BMI category, particularly NWT and OWT performed better than UWT suggests that in prescribing FR exercise, individuals in higher BMI category (NWT and OWT) may produce greater improvements in flexibility and hROM.

References Beardsley C, Škarabot J (2015) Effects of self-myofascial release: a systematic review. J Bodyw Mov Ther 19(4):747–758 Behara B, Jacobson BH (2017) Acute effects of deep tissue foam rolling and dynamic stretching on muscular strength, power, and flexibility in Division I Linemen. J Strength Cond Res 31(4):888– 892 Boguszewski D, Falkowska M, Adamczyk JG, Białoszewski D (2017) Influence of foam rolling on the functional limitations of the musculoskeletal system in healthy women. Biomed Human Kinet 9(1):75–81 Cox Z (2021) Flexibility: the forgotten component of fitness: eccentric exercise vs. static stretching to improve flexibility Do K, Yim J (2018) Acute effect of self-myofascial release using a foam roller on the plantar fascia on hamstring and lumbar spine superficial back line flexibility. Phys Ther Rehab Sci 7(1):35–40 Hodgson DD, Lima CD, Low JL, Behm DG (2018) Four weeks of roller massage training did not impact range of motion, pain pressure threshold, voluntary contractile properties or jump performance. Int J Sports Phys Ther 13(5):835 Junker DH, Stöggl TL (2015) The foam roll as a tool to improve hamstring flexibility. J Strength Cond Res 29(12):3480–3485 Kiyono R, Onuma R, Yasaka K, Sato S, Yahata K, Nakamura M (2020) Effects of 5-week foam rolling intervention on range of motion and muscle stiffness. J Strength Conditioning Res

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Konrad A, Nakamura M, Tilp M, Donti O, Behm DG (222) Foam rolling training effects on range of motion: a systematic review and meta-analysis. Sports Med, pp 1–13 Mohr AR, Long BC, Goad CL (2014) Effect of foam rolling and static stretching on passive hip-flexion range of motion. J Sport Rehabil 23(4):296–299 Norkin CC, White DJ (2016) Measurement of joint motion: a guide to goniometry. F.A. Davis Company Pearcey GE, Bradbury-Squires DJ, Kawamoto J-E, Drinkwater EJ, Behm DG, Button DC (2015) Foam rolling for delayed-onset muscle soreness and recovery of dynamic performance measures. J Athl Train 50(1):5–13 Reid DA, McNair PJ (2004) Passive force, angle, and stiffness changes after stretching of hamstring muscles. Med Sci Sports Exerc 36(11):1944–1948 Schleip R (2003) Fascial plasticity—a new neurobiological explanation: Part 1. J Bodyw Mov Ther 7(1):11–19 Shadmehr A, Hadian MR, Naiemi SS, Jalaie S (2009) Hamstring flexibility in young women following passive stretch and muscle energy technique. J Back Musculoskelet Rehabil 22(3):143–148 Smith JC, Pridgeon B, Hall MGC (2018) Acute effect of foam rolling and dynamic stretching on flexibility and jump height. J Strength Cond Res 32(8):2209–2215 Su H, Chang N-J, Wu W-L, Guo L-Y, Chu I-H (2017) Acute effects of foam rolling, static stretching, and dynamic stretching during warm-ups on muscular flexibility and strength in young adults. J Sport Rehabil 26(6):469–477 Sullivan KM, Silvey DB, Button DC, Behm DG (2013) Roller-massager application to the hamstrings increases sit-and-reach range of motion within five to ten seconds without performance impairments. Int J Sports Phys Ther 8(3):228 Tas S, Bek N, Ruhi Onur M, Korkusuz F (2017) Effects of body mass index on mechanical properties of the plantar fascia and heel pad in asymptomatic participants. Foot Ankle Int 38(7):779–784 Weerapong P, Hume PA, Kolt GS (2005) The mechanisms of massage and effects on performance, muscle recovery and injury prevention. Sports Med 35(3):235–256 Wells KF, Dillon EK (1952) The sit and reach—a test of back and leg flexibility. Res Q Am Assoc Health Phys Educ Recreation 23(1):115–118 Wiewelhove T, Döweling A, Schneider C, Hottenrott L, Meyer T, Kellmann M, Pfeiffer M, Ferrauti A (2019) A meta-analysis of the effects of foam rolling on performance and recovery. Front Physiol 10 World Health Organization (2000) Obesity: preventing and managing the global epidemic Yoshimura A, Schleip R, Hirose N (2020) Effects of self-massage using a foam roller on ankle range of motion and gastrocnemius fascicle length and muscle hardness: a pilot study. J Sport Rehabil 29(8):1171–1178

Effect of Cordyceps Militaris, Arginine and Citrulline Supplementation on Long Distance Runners in Hot Conditions Hui Yin Ler, Jian Yun Tan, and Kai Quin Chan

Abstract Cordyceps militaris (CM) contains cordycepin that improves mitochondrial biogenesis and ATP production, whereas arginine (Arg) and citrulline (Cit) show benefits in improving endothelial function in the human body. This study aimed to examine the effects of CM, Arg and Cit supplementation on endurance runners in hot conditions. Twenty-one runners (16 males; 5 females; age = 36.0 ± 1.6 yrs; VO2max = 53.2 ± 3.2 ml kg−1 min−1 ) were recruited, and they were randomly assigned into either: (i) AC (Arg and Cit: 2 g day−1 each) or (ii) AC + CM (Arg, Cit and CM (2 g day−1 each) or (iii) placebo groups. Subjects underwent one preliminary testing and three experimental trials in hot conditions: (i) Prolonged Exercise Testing (PET) without supplementation (PET-0), (ii) PET on Day-7 of supplementation (PET-7) and (iii) PET on Day-14 of supplementation (PET-14). The PET consists of 45 min of running at 65% of VO2max followed by an incremental exercise test. Results showed that subjects from the AC + CM group improved significantly during the incremental test from 10.7 ± 1.7 min (PET-7) to 11.4 ± 1.2 min (PET-14; p = 0.047). Oxygen uptake (VO2 ) during the 45-min run at PET-14 in the AC + CM group was significantly lower than PET-0 (33.4 ± 4.9 vs 30.9 ± 5.3 ml kg−1 min−1 ; p = 0.008). In conclusion, 14 days of AC + CM supplementation can improve endurance runners’ running economy and running performance under hot conditions. Keywords Running economy · Running performance · Thermoregulatory

1 Introduction Cordyceps is classified as a herb in traditional chinese medicine. There are several types of cordyceps species, but most of the research studies cordyceps sinensis and cordyceps militaris (Chiu et al. 2016; Hur 2008). The major bioactive compounds H. Y. Ler (B) · J. Y. Tan · K. Q. Chan Department of Sport Science, Faculty of Applied Sciences, Tunku Abdul Rahman University of Management and Technology, Kuala Lumpur, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. H. A. Hassan et al. (eds.), Proceedings of the 8th International Conference on Movement, Health and Exercise, Lecture Notes in Bioengineering, https://doi.org/10.1007/978-981-99-2162-1_32

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that can be found in Cordyceps militaris are cordycepin and polysaccharide (Chiu et al. 2016; Tuli et al. 2014). Research reported that cordyceps militaris contains 2.65 ± 0.02 mg g−1 of cordycepin and 2.45 ± 0.03 mg g−1 of adenosine from the fruiting bodies, whereas cordyceps sinensis contains 0.980 ± 0.01 mg g−1 of cordycepin and 1.64 ± 0.03 mg g−1 of adenosine from the fruiting bodies of Cordyceps sinensis (Huang et al. 2009), which are both lower than cordyceps militaris. The primary function of cordycepin is to activate 5’ adenosine monophosphate-protein kinase (AMPK) which in turn improves mitochondrial biogenesis and ATP production (Hawley et al. 2020). Moreover, cordyceps militaris also acts as an antioxidant property by reducing the oxidative stress in the muscles (Pingitore et al. 2015) and delays fatigue by improving the time to exhaustion in animal studies (Song et al. 2015). Researchers reported that arginine and citrulline showed beneficial effects in improving endothelial function in the human body through the regulation of endothelial nitric oxide synthase (eNOS) activity (Moncada and Higgs 1993; Wu and Morris 1998). The function of eNOS is to stimulate nitric oxide through the nitrite-nitratenitric oxide pathway and allow it to enter the bloodstream through the endothelial wall. It causes the endothelial wall to widen, or so-called vasodilation. It has been documented that arginine and citrulline supplements can improve sports performance by increasing the oxygenated blood flow to the working muscles. This can help improve muscle force production by producing more adenosine triphosphate (ATP) (Wu and Morris 1998; Chin-Dusting et al. 2007). It is well known that athletes who compete under hot conditions may decrease their sports performance because of the competition between the increase in skin blood flow to dissipate heat and the increase in muscle blood flow to extract oxygen and supply energy (Kenney et al. 2015). And exercise at high intensity under hot conditions increases free radical production, which in turn increases the oxidative stress in the muscles (Brooks et al. 2008). Sport performance can be decreased by oxidative stress by inhibiting mitochondrial biogenesis and reducing ATP production (Rossi et al. 2014). Cordyceps militaris can act as an antioxidant property (Hirsch et al. 2017), whereas arginine and citrulline could increase skin blood flow and help improve heat dissipation. However, the optimal dosage of these combined supplements for athletes is not clearly known. To our knowledge, only two studies investigated the effect of cordyceps militaris on human sport performance (Hirsch et al. 2017; Dudgeon et al. 2018). Hirsch et al. (2017) reported that 1-week of cordyceps militaris supplementation at 4 g d−1 did not significantly improve performance compared to a placebo (Hirsch et al. 2017). However, the 3-week supplementation period resulted in significant improvements in maximal oxygen consumption, with potential improvements in ventilatory threshold and time to exhaustion, suggesting the potential for greater benefits with chronic supplementation. Another study, with a dose of 1–2 g day−1 over 28 days, reported significant improvement in time to fatigue (26 ± 61 s) and 2.5% increase in VO2peak (Dudgeon et al. 2018). As the current study implemented a loading period of 2 weeks, and also considered the mixture effects of arginine and citrulline, therefore a dosage of 2 g day−1 of cordyceps militaris was examined.

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This present study aimed to examine the effects of cordyceps militaris, arginine, and citrulline supplementation on endurance runners in hot conditions. We hypothesized that the combination of these three supplements allows athletes to regulate their thermoregulatory responses efficiently under hot conditions.

2 Methods 2.1 Subject Twenty-one long distance runners (16 males; 5 females; age = 36.0 ± 1.6 yrs; VO2max = 53.2 ± 3.2 ml kg−1 .min−1 ) were recruited for this study. A power calculation using G*Power 3 software (Heinrich-Heine-Universitat Düsseldorf, Germany) was performed with an α-level of 0.05, a power value of 0.80 and an effect size of 0.88, determined from the smallest significant difference in the primary outcome variable (TQR) from the previous studies employing a similar protocol (Hawley et al. 2020). A minimum sample size of six individuals for each group was determined. Therefore, 21 subjects were recruited for this present study. However, two subjects from the placebo group did not manage to complete the last experimental trials due to COVID-19. Subjects who participated in this study agreed to refrain from taking nutritional supplements for at least two weeks prior to the study and during all the experimental trials. Subjects were advised to continue their usual diet and training regime throughout the study. Prior to testing, subjects were told to fast for eight hours and refrain from any vigorous exercise for 24 h. The study protocol was reviewed and approved by the Tunku Abdul Rahman University College Ethics Committee (FOAS/EC/2019/03-17).

2.2 Experimental Design A double-blind randomized controlled experimental design was used in this study. Subjects were randomly assigned into either: (i) AC (Arg and Cit: 2 g day−1 each; mixed with berry juice powder) or (ii) AC + CM (Arg, Cit and CM; 2 g day−1 each; mixed with berry juice powder) or (iii) placebo (berry juice powder) groups. These products were prepared by Enercan Sdn Bhd. Subjects and researchers were blinded to the treatment assignment to eliminate confounding by co-interventions. Each of the subjects were required to run through one preliminary test and three experimental trials under hot conditions (33 ± 3 °C): (i) Prolonged Exercise Testing at Baseline (PET-0), (ii) Prolonged Exercise Testing at Day 7 (PET-7) and (iii) Prolonged Exercise Testing at Day 14 (PET-14). During each of the experimental trials, subjects were required to complete a Prolonged Exercise Testing (PET) which consists of 45 min at constant speed at 65% of VO2max and followed by an incremental exercise test.

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Subjects were allowed to rest for 5 min after PET and continue with the incremental exercise test.

2.3 Preliminary Testing Prior to the preliminary testing, subjects were required to fill out the Physical Activity Readiness Questionnaire (PAR-Q). The researcher explained the participation information sheet to understand the risks, procedures, and benefits of the study, and consent was obtained. Body composition was measured using a bioelectrical impedance analyzer (InBody 570, Korea). Height was measured using the digital free-standing stadiometer (InBody, BSM170, Korea). To determine the exercise intensity (running speed of 65% VO2max ) and fitness level of the subjects, they were required to perform a submaximal exercise test and a maximal oxygen uptake (VO2max ) test. For the submaximal test, subjects were required to run on the treadmill for 16 min with four stages. The speed of each stage will be increased by 1.5 km hr−1 every 4 min. Oxygen uptake (VO2 ), respiratory exchange ratio (RER), rating of perceived exertion (RPE) and heart rate (HR) responses were collected 30 s before moving on to the next stage. After the submaximal test, the subjects were allowed to rest for 5 min followed by an incremental treadmill run with an increment of 2% every 2-min until exhaustion. VO2 , RER, RPE and HR were collected for every last 15 s of each stage. During the last of each stage of the run. HRmax , VO2max , time to exhaustion, and RPE were all obtained within the final 10 s of running at the point of volitional fatigue.

2.4 Experimental Trials To increase the ambient temperature in the laboratory, two heated lamps were placed on the top of the treadmill and adjusted to approximately 33 °C. The ambient temperature and humidity were monitored throughout the study using a weather meter (Kestrel 4000 Series, Nielsen-Kellerman Company, USA). Subjects were required to ingest either: (i) AC (Arg and Cit: 2 g day−1 each) or (ii) AC + CM (Arg, Cit and CM; 2 g day−1 each) or (iii) placebo for 14 days (Table 1). These supplements were mixed with berry juice powder and were given to subjects in sachet packaging. Subjects were instructed to mix one sachet with 200 ml of plain water and consume after breakfast and after lunch. A day before the experimental trials, subjects were reminded not to take any caffeine and not perform any strenuous physical activity for at least 24 h prior to the trial. Furthermore, subjects were reminded to stay hydrated by drinking 6 mL kg BW−1 every 3 h, 4–5 sessions per day of water on the day before and during the day of testing. Upon arrival at the laboratory, subjects were required to consume one sachet containing Arg, Cit and CM (AC + CM group) or Arg and Cit (AC group) or placebo

Effect of Cordyceps Militaris, Arginine and Citrulline Supplementation … Table 1 Bioactive components of three groups of supplementations

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Bioactive components

Group AC + CM (g day−1 )

AC (g day−1 )

P (g day−1 )

Cordyceps Militaris

2

–

–

L-Arginine

2

2

–

L-Citrulline

2

2

–

(P group) 60 min prior to the testing (PET-7 and PET-14 trials). Subjects’ weight, resting HR and resting BP were recorded. Finger prick blood samples and urine samples were collected to determine glucose level and urine specific gravity analysis to ensure subjects were well hydrated before the start of the trial and at the end of the trial. A temperature probe was inserted 10 cm beyond the anal sphincter of the subject to determine the core temperature (T core ). Four thermistors (Thermochron iButton® DS1291H; Maxim/Dallas Semiconductor Corp., USA) were placed on the subject’s arm, chest, thigh, and back calf to measure the skin temperatures (T sk ). The readings of skin and core temperatures were recorded every 5 min during the trials. A HR monitor was placed in the front chest of the subject, and the VO2 testing mask which is connected to the Metabolic Cart (Quark CPET, Italy) was placed on the face of the subject. For PETs, subjects were required to run at a constant speed on the treadmill for 45 min at 65% of VO2 max and 1% inclination under hot conditions with ~33 °C. To ensure the subject is running at a similar energy expenditure to outdoor running, the treadmill gradient should be increased by 1% to show similar energy expenditure with outdoor running (Jones et al. 1996). HR, VO2 , T core , T skin responses were monitored throughout the run, whereas RPE and thermal sensation data were recorded every 5 min of the run using the Borg Scale and ASHRAE Scale, respectively. After 45 min of constant speed running, subjects rested for 5 min, followed by an incremental exercise test. The treadmill’s inclination increased by 2% every stage (2 min) until exhaustion. Encouragement was provided to the subjects, which will motivate them to run at their maximal effort. Subjects were required to repeat the same procedures at day 7 of ingestion (PET-7) and day 14 (PET-14) of ingestion.

2.5 Statistical Analysis Statistical analysis was performed by using IBM SPSS 26.0 (Statistical Product and Service Solutions). One-way ANOVA test was used to determine between groups in each trial, while two-way ANOVA test was used to determine any occurrence of mean difference between each time and groups. When a significant interaction was found, paired samples t-test was used to identify the difference between means. All

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Fig. 1 Time to exhaustion during incremental exercise test of PET-0, PET-7 and PET-14 trials. *Significantly different from PET-7 (p < 0.05)

values are expressed as mean ± SD and the significance level was accepted at p < 0.05.

3 Results 3.1 Time to Exhaustion Figure 1 showed the AC + CM group significantly improved their running performance by 6.0% at PET-14 as compared to PET-7 (p = 0.047).

3.2 Heart Rate Responses Table 2 showed the HR responses in P, AC and AC + CM groups were similar throughout the 45-min PET (p > 0.05).

Effect of Cordyceps Militaris, Arginine and Citrulline Supplementation … Table 2 Mean heart rate responses during 45-min of Prolonged Exercise Test (PET)

Group/trial

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Heart rate (beats min−1 ) P

AC

AC + CM

PET-0

149 ± 20

153 ± 15

137 ± 17

PET-7

146 ± 26

152 ± 16

134 ± 17

PET-14

148 ± 21

151 ± 14

135 ± 17

Table 3 Mean VO2 responses during 45-min of Prolonged Exercise Test (PET) VO2 (ml kg−1 min−1 )

Group/trial

P

AC

AC + CM

PET-0

33.2 ± 2.4

35.6 ± 6.2

33.4 ± 4.9

PET-7

33.5 ± 3.3

35.2 ± 4.7

32.2 ± 4.9

PET-14

32.1 ± 2.2

33.1 ± 5.2

30.9 ± 5.3**

** Significantly

different from PET-0 (p < 0.01)

Table 4 Mean VO2peak responses during Incremental Tests Group/trial

VO2 Peak (ml kg−1 min−1 ) P

% VO2max

AC

% VO2max

AC + CM

% VO2max

PET-0

47.2 ± 9.3

95.0

50.8 ± 10

90.4

53.3 ± 6.5

99.3

PET-7

48.1 ± 10.4

96.7

48.7 ± 5.7

86.7

51.7 ± 8.3

96.3

PET-14

44.8 ± 7.8

90.1

48.8 ± 7.0

86.8

52.6 ± 8.3

97.9

3.3 Oxygen Uptake (VO2 ) Responses Table 3 showed VO2 responses were significantly lower in PET-14 (33.4 ± 4.9 ml kg−1 .min−1 ) as compared to PET-0 (30.9 ± 5.3 ml kg−1 .min−1 ) in the AC + CM group by 2 ml kg−1 .min−1 (p = 0.008), whereas other groups remained similar for all trials (p > 0.05) during 45-min of PETs. Table 4 shows the peak oxygen uptake during the incremental test in P, AC and AC + CM groups was similar (p > 0.05). However, subjects from the AC + CM groups were able to run closer to their VO2max than the other two groups under hot conditions.

3.4 Thermoregulatory Response (Core Temperature and Skin Temperature) The results showed the core temperature and skin temperatures responses in P, AC and AC + CM groups were similar throughout the 45-min PET (p > 0.05). Core

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temperatures were maintained at ~38 °C and mean skin temperatures were maintained at ~34 °C during all experimental trials.

3.5 Perceptual Responses (RPE and Thermal Sensation) Similarly, the rate of perceived exertion (RPE) responses in P (PET-0 = 9.7 ± 2.3; PET-7 = 10.3 ± 2.8; PET-14 = 9.2 ± 2.6), AC (PET-0 = 9.0 ± 1.9; PET-7 = 9.0 ± 2.5; PET-14 = 8.6 ± 1.8) and AC + CM (PET-0 = 8.6 ± 1.8; PET-7 = 8.3 ± 2.4; PET-14 = 8.2 ± 2.2) groups were similar throughout the 45-min PET (p > 0.05). For thermal sensation, subjects from the AC group perceived cooler temperatures during PET-14 as compared to PET-0 (1.3 ± 0.4 vs. 0.9 ± 0.4; p = 0.026), whereas the other groups perceived the ambient conditions were “slightly warm” (p > 0.05).

4 Discussion To our knowledge, no study has examined the combination effects of cordyceps militaris, arginine and citrulline supplements on endurance performance in hot conditions. The results of this present study showed that with the ingestion of Cordyceps militaris, arginine and citrulline (2 g day−1 each) for 14 days, running performance of the incremental test was significantly improved by 6.0% (p = 0.047) (Fig. 1). Research demonstrated that supplementing for one week with a Cordyceps militaris-containing mushroom blend at 4 g day−1 did not significantly enhance performance compared to a placebo (Hirsch et al. 2017). The potential for higher advantages with chronic supplementation was suggested by the exploratory threeweek supplementation period, which led to significant improvements in maximum oxygen consumption and tolerance to high-intensity exercise. Research suggested that there is a need for higher dosage of cordyceps militaris (more than 4 g day−1 ) in order to show significant improvement in exercise performance (Hirsch et al. 2017). Another research reported that there was a significant improvement in exercise performance with 1.5 g day−1 after 28 days of cordyceps militaris ingestion in 40 young adult (19–34 yrs) subjects (Dudgeon et al. 2018). Subjects who consumed cordyceps militaris experienced a significant 3 bpm drop in economy heart rate from pre- to post-testing (p < 0.05). The authors suggested that a longer duration, lower dose (1.5 g day−1 ) appears to improve endurance performance in healthy young adults. Further, short duration supplementation of higher doses may improve performance, but differing effects may occur based upon fitness level. In the present study, subjects were required to ingest cordyceps militaris, arginine and citrulline (2 g day−1 each) for 14 days experienced improvement in time to exhaustion and running economy. This indicated that cordyceps militaris may have a beneficial effect on improving mitochondrial biogenesis and ATP production during prolonged exercise under hot conditions.

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A study reported that there was an improvement in 10-min full-power pedaling test at day 7 of arginine and citrulline (both 1.2 g day−1 each) ingestion (Suzuki et al. 2019). In addition, subjective perceptions of “leg muscle soreness” and “ease of pedaling” were also significantly improved. It was postulated that citrulline or the resulting nitric oxide could influence subjective perceptions, and the mechanism behind this requires further investigation. Similarly, results from this present study showed that subjects of the AC group reported “slightly cool” during PET-14, whereas the other groups perceived the ambient circumstances were "slightly warm" throughout the experimental trials, even if their T core and T skin responses were similar to those of the other groups. These results showed that arginine and citrulline increased skin blood flow and helped in improving heat dissipation during experimental trials.

5 Conclusion Oral ingestion of cordyceps militaris, arginine and citrulline at doses of 2.0 g day−1 each for 14 days improved exercise performance in the incremental test, running economy during 45-min of steady-state running under hot conditions. It was speculated that the increased mitochondrial biogenesis and ATP production due to the induction by cordycepin and the improvement of endothelial function induced by arginine and citrulline could account for this effect. Endurance sports athletes can consider this combination as one of the ergogenic aids to optimize their sport performance in the heat. Furthermore, the dosage of cordyceps militaris, arginine and citrulline prescribed in this study can be used as reference for sport nutritionists or researchers. Future studies should aim to establish dosage of cordyceps militaris, arginine and citrulline for maximal ergogenic benefits. Acknowledgements The authors would like to thank the subjects who participated in this research project. Financial Support and Sponsorship The supplementations [Placebo, AC, and AC + CM (Mitoceps Plus)] of this research project were sponsored by Enercan Sdn Bhd.

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